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Helsinki-NLP/opus-mt-tc-big-itc-itc
Helsinki-NLP
2023-10-10T10:56:12Z
141
0
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "ast", "ca", "es", "fr", "gl", "it", "lad", "oc", "pms", "pt", "ro", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-08-12T10:02:43Z
--- language: - ast - ca - es - fr - gl - it - lad - oc - pms - pt - ro tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-itc-itc results: - task: name: Translation ast-cat type: translation args: ast-cat dataset: name: flores101-devtest type: flores_101 args: ast cat devtest metrics: - name: BLEU type: bleu value: 31.8 - name: chr-F type: chrf value: 0.57870 - task: name: Translation ast-fra type: translation args: ast-fra dataset: name: flores101-devtest type: flores_101 args: ast fra devtest metrics: - name: BLEU type: bleu value: 31.1 - name: chr-F type: chrf value: 0.56761 - task: name: Translation ast-glg type: translation args: ast-glg dataset: name: flores101-devtest type: flores_101 args: ast glg devtest metrics: - name: BLEU type: bleu value: 27.9 - name: chr-F type: chrf value: 0.55161 - task: name: Translation ast-ita type: translation args: ast-ita dataset: name: flores101-devtest type: flores_101 args: ast ita devtest metrics: - name: BLEU type: bleu value: 22.1 - name: chr-F type: chrf value: 0.51764 - task: name: Translation ast-oci type: translation args: ast-oci dataset: name: flores101-devtest type: flores_101 args: ast oci devtest metrics: - name: BLEU type: bleu value: 20.6 - name: chr-F type: chrf value: 0.49545 - task: name: Translation ast-por type: translation args: ast-por dataset: name: flores101-devtest type: flores_101 args: ast por devtest metrics: - name: BLEU type: bleu value: 31.5 - name: chr-F type: chrf value: 0.57347 - task: name: Translation ast-ron type: translation args: ast-ron dataset: name: flores101-devtest type: flores_101 args: ast ron devtest metrics: - name: BLEU type: bleu value: 24.8 - name: chr-F type: chrf value: 0.52317 - task: name: Translation ast-spa type: translation args: ast-spa dataset: name: flores101-devtest type: flores_101 args: ast spa devtest metrics: - name: BLEU type: bleu value: 21.2 - name: chr-F type: chrf value: 0.49741 - task: name: Translation cat-ast type: translation args: cat-ast dataset: name: flores101-devtest type: flores_101 args: cat ast devtest metrics: - name: BLEU type: bleu value: 24.7 - name: chr-F type: chrf value: 0.56754 - task: name: Translation cat-fra type: translation args: cat-fra dataset: name: flores101-devtest type: flores_101 args: cat fra devtest metrics: - name: BLEU type: bleu value: 38.4 - name: chr-F type: chrf value: 0.63368 - task: name: Translation cat-glg type: translation args: cat-glg dataset: name: flores101-devtest type: flores_101 args: cat glg devtest metrics: - name: BLEU type: bleu value: 32.2 - name: chr-F type: chrf value: 0.59596 - task: name: Translation cat-ita type: translation args: cat-ita dataset: name: flores101-devtest type: flores_101 args: cat ita devtest metrics: - name: BLEU type: bleu value: 26.3 - name: chr-F type: chrf value: 0.55886 - task: name: Translation cat-oci type: translation args: cat-oci dataset: name: flores101-devtest type: flores_101 args: cat oci devtest metrics: - name: BLEU type: bleu value: 24.6 - name: chr-F type: chrf value: 0.54285 - task: name: Translation cat-por type: translation args: cat-por dataset: name: flores101-devtest type: flores_101 args: cat por devtest metrics: - name: BLEU type: bleu value: 37.7 - name: chr-F type: chrf value: 0.62913 - task: name: Translation cat-ron type: translation args: cat-ron dataset: name: flores101-devtest type: flores_101 args: cat ron devtest metrics: - name: BLEU type: bleu value: 29.5 - name: chr-F type: chrf value: 0.56885 - task: name: Translation cat-spa type: translation args: cat-spa dataset: name: flores101-devtest type: flores_101 args: cat spa devtest metrics: - name: BLEU type: bleu value: 24.6 - name: chr-F type: chrf value: 0.53372 - task: name: Translation fra-ast type: translation args: fra-ast dataset: name: flores101-devtest type: flores_101 args: fra ast devtest metrics: - name: BLEU type: bleu value: 20.7 - name: chr-F type: chrf value: 0.52696 - task: name: Translation fra-cat type: translation args: fra-cat dataset: name: flores101-devtest type: flores_101 args: fra cat devtest metrics: - name: BLEU type: bleu value: 34.6 - name: chr-F type: chrf value: 0.60492 - task: name: Translation fra-glg type: translation args: fra-glg dataset: name: flores101-devtest type: flores_101 args: fra glg devtest metrics: - name: BLEU type: bleu value: 30.3 - name: chr-F type: chrf value: 0.57485 - task: name: Translation fra-ita type: translation args: fra-ita dataset: name: flores101-devtest type: flores_101 args: fra ita devtest metrics: - name: BLEU type: bleu value: 27.3 - name: chr-F type: chrf value: 0.56493 - task: name: Translation fra-oci type: translation args: fra-oci dataset: name: flores101-devtest type: flores_101 args: fra oci devtest metrics: - name: BLEU type: bleu value: 28.2 - name: chr-F type: chrf value: 0.57449 - task: name: Translation fra-por type: translation args: fra-por dataset: name: flores101-devtest type: flores_101 args: fra por devtest metrics: - name: BLEU type: bleu value: 36.9 - name: chr-F type: chrf value: 0.62211 - task: name: Translation fra-ron type: translation args: fra-ron dataset: name: flores101-devtest type: flores_101 args: fra ron devtest metrics: - name: BLEU type: bleu value: 29.4 - name: chr-F type: chrf value: 0.56998 - task: name: Translation fra-spa type: translation args: fra-spa dataset: name: flores101-devtest type: flores_101 args: fra spa devtest metrics: - name: BLEU type: bleu value: 24.2 - name: chr-F type: chrf value: 0.52880 - task: name: Translation glg-ast type: translation args: glg-ast dataset: name: flores101-devtest type: flores_101 args: glg ast devtest metrics: - name: BLEU type: bleu value: 22.4 - name: chr-F type: chrf value: 0.55090 - task: name: Translation glg-cat type: translation args: glg-cat dataset: name: flores101-devtest type: flores_101 args: glg cat devtest metrics: - name: BLEU type: bleu value: 32.6 - name: chr-F type: chrf value: 0.60550 - task: name: Translation glg-fra type: translation args: glg-fra dataset: name: flores101-devtest type: flores_101 args: glg fra devtest metrics: - name: BLEU type: bleu value: 36.0 - name: chr-F type: chrf value: 0.62026 - task: name: Translation glg-ita type: translation args: glg-ita dataset: name: flores101-devtest type: flores_101 args: glg ita devtest metrics: - name: BLEU type: bleu value: 25.9 - name: chr-F type: chrf value: 0.55834 - task: name: Translation glg-oci type: translation args: glg-oci dataset: name: flores101-devtest type: flores_101 args: glg oci devtest metrics: - name: BLEU type: bleu value: 21.9 - name: chr-F type: chrf value: 0.52520 - task: name: Translation glg-por type: translation args: glg-por dataset: name: flores101-devtest type: flores_101 args: glg por devtest metrics: - name: BLEU type: bleu value: 32.7 - name: chr-F type: chrf value: 0.60027 - task: name: Translation glg-ron type: translation args: glg-ron dataset: name: flores101-devtest type: flores_101 args: glg ron devtest metrics: - name: BLEU type: bleu value: 27.8 - name: chr-F type: chrf value: 0.55621 - task: name: Translation glg-spa type: translation args: glg-spa dataset: name: flores101-devtest type: flores_101 args: glg spa devtest metrics: - name: BLEU type: bleu value: 24.4 - name: chr-F type: chrf value: 0.53219 - task: name: Translation ita-ast type: translation args: ita-ast dataset: name: flores101-devtest type: flores_101 args: ita ast devtest metrics: - name: BLEU type: bleu value: 17.1 - name: chr-F type: chrf value: 0.50741 - task: name: Translation ita-cat type: translation args: ita-cat dataset: name: flores101-devtest type: flores_101 args: ita cat devtest metrics: - name: BLEU type: bleu value: 27.9 - name: chr-F type: chrf value: 0.57061 - task: name: Translation ita-fra type: translation args: ita-fra dataset: name: flores101-devtest type: flores_101 args: ita fra devtest metrics: - name: BLEU type: bleu value: 32.0 - name: chr-F type: chrf value: 0.60199 - task: name: Translation ita-glg type: translation args: ita-glg dataset: name: flores101-devtest type: flores_101 args: ita glg devtest metrics: - name: BLEU type: bleu value: 25.9 - name: chr-F type: chrf value: 0.55312 - task: name: Translation ita-oci type: translation args: ita-oci dataset: name: flores101-devtest type: flores_101 args: ita oci devtest metrics: - name: BLEU type: bleu value: 18.1 - name: chr-F type: chrf value: 0.48447 - task: name: Translation ita-por type: translation args: ita-por dataset: name: flores101-devtest type: flores_101 args: ita por devtest metrics: - name: BLEU type: bleu value: 29.0 - name: chr-F type: chrf value: 0.58162 - task: name: Translation ita-ron type: translation args: ita-ron dataset: name: flores101-devtest type: flores_101 args: ita ron devtest metrics: - name: BLEU type: bleu value: 24.2 - name: chr-F type: chrf value: 0.53703 - task: name: Translation ita-spa type: translation args: ita-spa dataset: name: flores101-devtest type: flores_101 args: ita spa devtest metrics: - name: BLEU type: bleu value: 23.1 - name: chr-F type: chrf value: 0.52238 - task: name: Translation oci-ast type: translation args: oci-ast dataset: name: flores101-devtest type: flores_101 args: oci ast devtest metrics: - name: BLEU type: bleu value: 20.2 - name: chr-F type: chrf value: 0.53010 - task: name: Translation oci-cat type: translation args: oci-cat dataset: name: flores101-devtest type: flores_101 args: oci cat devtest metrics: - name: BLEU type: bleu value: 32.2 - name: chr-F type: chrf value: 0.59946 - task: name: Translation oci-fra type: translation args: oci-fra dataset: name: flores101-devtest type: flores_101 args: oci fra devtest metrics: - name: BLEU type: bleu value: 39.0 - name: chr-F type: chrf value: 0.64290 - task: name: Translation oci-glg type: translation args: oci-glg dataset: name: flores101-devtest type: flores_101 args: oci glg devtest metrics: - name: BLEU type: bleu value: 28.0 - name: chr-F type: chrf value: 0.56737 - task: name: Translation oci-ita type: translation args: oci-ita dataset: name: flores101-devtest type: flores_101 args: oci ita devtest metrics: - name: BLEU type: bleu value: 24.2 - name: chr-F type: chrf value: 0.54220 - task: name: Translation oci-por type: translation args: oci-por dataset: name: flores101-devtest type: flores_101 args: oci por devtest metrics: - name: BLEU type: bleu value: 35.7 - name: chr-F type: chrf value: 0.62127 - task: name: Translation oci-ron type: translation args: oci-ron dataset: name: flores101-devtest type: flores_101 args: oci ron devtest metrics: - name: BLEU type: bleu value: 28.0 - name: chr-F type: chrf value: 0.55906 - task: name: Translation oci-spa type: translation args: oci-spa dataset: name: flores101-devtest type: flores_101 args: oci spa devtest metrics: - name: BLEU type: bleu value: 22.8 - name: chr-F type: chrf value: 0.52110 - task: name: Translation por-ast type: translation args: por-ast dataset: name: flores101-devtest type: flores_101 args: por ast devtest metrics: - name: BLEU type: bleu value: 22.5 - name: chr-F type: chrf value: 0.54539 - task: name: Translation por-cat type: translation args: por-cat dataset: name: flores101-devtest type: flores_101 args: por cat devtest metrics: - name: BLEU type: bleu value: 36.4 - name: chr-F type: chrf value: 0.61809 - task: name: Translation por-fra type: translation args: por-fra dataset: name: flores101-devtest type: flores_101 args: por fra devtest metrics: - name: BLEU type: bleu value: 39.7 - name: chr-F type: chrf value: 0.64343 - task: name: Translation por-glg type: translation args: por-glg dataset: name: flores101-devtest type: flores_101 args: por glg devtest metrics: - name: BLEU type: bleu value: 30.4 - name: chr-F type: chrf value: 0.57965 - task: name: Translation por-ita type: translation args: por-ita dataset: name: flores101-devtest type: flores_101 args: por ita devtest metrics: - name: BLEU type: bleu value: 26.3 - name: chr-F type: chrf value: 0.55841 - task: name: Translation por-oci type: translation args: por-oci dataset: name: flores101-devtest type: flores_101 args: por oci devtest metrics: - name: BLEU type: bleu value: 25.3 - name: chr-F type: chrf value: 0.54829 - task: name: Translation por-ron type: translation args: por-ron dataset: name: flores101-devtest type: flores_101 args: por ron devtest metrics: - name: BLEU type: bleu value: 29.8 - name: chr-F type: chrf value: 0.57283 - task: name: Translation por-spa type: translation args: por-spa dataset: name: flores101-devtest type: flores_101 args: por spa devtest metrics: - name: BLEU type: bleu value: 25.2 - name: chr-F type: chrf value: 0.53513 - task: name: Translation ron-ast type: translation args: ron-ast dataset: name: flores101-devtest type: flores_101 args: ron ast devtest metrics: - name: BLEU type: bleu value: 20.1 - name: chr-F type: chrf value: 0.52265 - task: name: Translation ron-cat type: translation args: ron-cat dataset: name: flores101-devtest type: flores_101 args: ron cat devtest metrics: - name: BLEU type: bleu value: 32.6 - name: chr-F type: chrf value: 0.59689 - task: name: Translation ron-fra type: translation args: ron-fra dataset: name: flores101-devtest type: flores_101 args: ron fra devtest metrics: - name: BLEU type: bleu value: 37.4 - name: chr-F type: chrf value: 0.63060 - task: name: Translation ron-glg type: translation args: ron-glg dataset: name: flores101-devtest type: flores_101 args: ron glg devtest metrics: - name: BLEU type: bleu value: 29.3 - name: chr-F type: chrf value: 0.56677 - task: name: Translation ron-ita type: translation args: ron-ita dataset: name: flores101-devtest type: flores_101 args: ron ita devtest metrics: - name: BLEU type: bleu value: 25.6 - name: chr-F type: chrf value: 0.55485 - task: name: Translation ron-oci type: translation args: ron-oci dataset: name: flores101-devtest type: flores_101 args: ron oci devtest metrics: - name: BLEU type: bleu value: 21.8 - name: chr-F type: chrf value: 0.52433 - task: name: Translation ron-por type: translation args: ron-por dataset: name: flores101-devtest type: flores_101 args: ron por devtest metrics: - name: BLEU type: bleu value: 36.1 - name: chr-F type: chrf value: 0.61831 - task: name: Translation ron-spa type: translation args: ron-spa dataset: name: flores101-devtest type: flores_101 args: ron spa devtest metrics: - name: BLEU type: bleu value: 24.1 - name: chr-F type: chrf value: 0.52712 - task: name: Translation spa-ast type: translation args: spa-ast dataset: name: flores101-devtest type: flores_101 args: spa ast devtest metrics: - name: BLEU type: bleu value: 15.7 - name: chr-F type: chrf value: 0.49008 - task: name: Translation spa-cat type: translation args: spa-cat dataset: name: flores101-devtest type: flores_101 args: spa cat devtest metrics: - name: BLEU type: bleu value: 23.2 - name: chr-F type: chrf value: 0.53905 - task: name: Translation spa-fra type: translation args: spa-fra dataset: name: flores101-devtest type: flores_101 args: spa fra devtest metrics: - name: BLEU type: bleu value: 27.4 - name: chr-F type: chrf value: 0.57078 - task: name: Translation spa-glg type: translation args: spa-glg dataset: name: flores101-devtest type: flores_101 args: spa glg devtest metrics: - name: BLEU type: bleu value: 22.0 - name: chr-F type: chrf value: 0.52563 - task: name: Translation spa-ita type: translation args: spa-ita dataset: name: flores101-devtest type: flores_101 args: spa ita devtest metrics: - name: BLEU type: bleu value: 22.3 - name: chr-F type: chrf value: 0.52783 - task: name: Translation spa-oci type: translation args: spa-oci dataset: name: flores101-devtest type: flores_101 args: spa oci devtest metrics: - name: BLEU type: bleu value: 16.3 - name: chr-F type: chrf value: 0.48064 - task: name: Translation spa-por type: translation args: spa-por dataset: name: flores101-devtest type: flores_101 args: spa por devtest metrics: - name: BLEU type: bleu value: 25.8 - name: chr-F type: chrf value: 0.55736 - task: name: Translation spa-ron type: translation args: spa-ron dataset: name: flores101-devtest type: flores_101 args: spa ron devtest metrics: - name: BLEU type: bleu value: 21.4 - name: chr-F type: chrf value: 0.51623 - task: name: Translation fra-spa type: translation args: fra-spa dataset: name: news-test2008 type: news-test2008 args: fra-spa metrics: - name: BLEU type: bleu value: 33.9 - name: chr-F type: chrf value: 0.58939 - task: name: Translation spa-fra type: translation args: spa-fra dataset: name: news-test2008 type: news-test2008 args: spa-fra metrics: - name: BLEU type: bleu value: 32.4 - name: chr-F type: chrf value: 0.58695 - task: name: Translation cat-fra type: translation args: cat-fra dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: cat-fra metrics: - name: BLEU type: bleu value: 54.6 - name: chr-F type: chrf value: 0.71201 - task: name: Translation cat-ita type: translation args: cat-ita dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: cat-ita metrics: - name: BLEU type: bleu value: 58.4 - name: chr-F type: chrf value: 0.74198 - task: name: Translation cat-por type: translation args: cat-por dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: cat-por metrics: - name: BLEU type: bleu value: 57.4 - name: chr-F type: chrf value: 0.74930 - task: name: Translation cat-spa type: translation args: cat-spa dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: cat-spa metrics: - name: BLEU type: bleu value: 78.1 - name: chr-F type: chrf value: 0.87844 - task: name: Translation fra-cat type: translation args: fra-cat dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: fra-cat metrics: - name: BLEU type: bleu value: 46.2 - name: chr-F type: chrf value: 0.66525 - task: name: Translation fra-ita type: translation args: fra-ita dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: fra-ita metrics: - name: BLEU type: bleu value: 53.8 - name: chr-F type: chrf value: 0.72742 - task: name: Translation fra-por type: translation args: fra-por dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: fra-por metrics: - name: BLEU type: bleu value: 48.6 - name: chr-F type: chrf value: 0.68413 - task: name: Translation fra-ron type: translation args: fra-ron dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: fra-ron metrics: - name: BLEU type: bleu value: 44.0 - name: chr-F type: chrf value: 0.65009 - task: name: Translation fra-spa type: translation args: fra-spa dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: fra-spa metrics: - name: BLEU type: bleu value: 54.8 - name: chr-F type: chrf value: 0.72080 - task: name: Translation glg-por type: translation args: glg-por dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: glg-por metrics: - name: BLEU type: bleu value: 61.1 - name: chr-F type: chrf value: 0.76720 - task: name: Translation glg-spa type: translation args: glg-spa dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: glg-spa metrics: - name: BLEU type: bleu value: 71.7 - name: chr-F type: chrf value: 0.82362 - task: name: Translation ita-cat type: translation args: ita-cat dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ita-cat metrics: - name: BLEU type: bleu value: 56.4 - name: chr-F type: chrf value: 0.72529 - task: name: Translation ita-fra type: translation args: ita-fra dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ita-fra metrics: - name: BLEU type: bleu value: 65.2 - name: chr-F type: chrf value: 0.77932 - task: name: Translation ita-por type: translation args: ita-por dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ita-por metrics: - name: BLEU type: bleu value: 54.0 - name: chr-F type: chrf value: 0.72798 - task: name: Translation ita-ron type: translation args: ita-ron dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ita-ron metrics: - name: BLEU type: bleu value: 51.1 - name: chr-F type: chrf value: 0.70814 - task: name: Translation ita-spa type: translation args: ita-spa dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ita-spa metrics: - name: BLEU type: bleu value: 62.9 - name: chr-F type: chrf value: 0.77455 - task: name: Translation lad-spa type: translation args: lad-spa dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: lad-spa metrics: - name: BLEU type: bleu value: 34.7 - name: chr-F type: chrf value: 0.52243 - task: name: Translation lad_Latn-spa type: translation args: lad_Latn-spa dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: lad_Latn-spa metrics: - name: BLEU type: bleu value: 42.6 - name: chr-F type: chrf value: 0.59363 - task: name: Translation oci-fra type: translation args: oci-fra dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: oci-fra metrics: - name: BLEU type: bleu value: 29.6 - name: chr-F type: chrf value: 0.49660 - task: name: Translation pms-ita type: translation args: pms-ita dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: pms-ita metrics: - name: BLEU type: bleu value: 20.0 - name: chr-F type: chrf value: 0.40221 - task: name: Translation por-cat type: translation args: por-cat dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: por-cat metrics: - name: BLEU type: bleu value: 52.2 - name: chr-F type: chrf value: 0.71146 - task: name: Translation por-fra type: translation args: por-fra dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: por-fra metrics: - name: BLEU type: bleu value: 60.9 - name: chr-F type: chrf value: 0.75565 - task: name: Translation por-glg type: translation args: por-glg dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: por-glg metrics: - name: BLEU type: bleu value: 59.0 - name: chr-F type: chrf value: 0.75348 - task: name: Translation por-ita type: translation args: por-ita dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: por-ita metrics: - name: BLEU type: bleu value: 58.8 - name: chr-F type: chrf value: 0.76883 - task: name: Translation por-ron type: translation args: por-ron dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: por-ron metrics: - name: BLEU type: bleu value: 46.6 - name: chr-F type: chrf value: 0.67838 - task: name: Translation por-spa type: translation args: por-spa dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: por-spa metrics: - name: BLEU type: bleu value: 64.8 - name: chr-F type: chrf value: 0.79336 - task: name: Translation ron-fra type: translation args: ron-fra dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ron-fra metrics: - name: BLEU type: bleu value: 55.0 - name: chr-F type: chrf value: 0.70307 - task: name: Translation ron-ita type: translation args: ron-ita dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ron-ita metrics: - name: BLEU type: bleu value: 53.7 - name: chr-F type: chrf value: 0.73862 - task: name: Translation ron-por type: translation args: ron-por dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ron-por metrics: - name: BLEU type: bleu value: 50.7 - name: chr-F type: chrf value: 0.70889 - task: name: Translation ron-spa type: translation args: ron-spa dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ron-spa metrics: - name: BLEU type: bleu value: 57.2 - name: chr-F type: chrf value: 0.73529 - task: name: Translation spa-cat type: translation args: spa-cat dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: spa-cat metrics: - name: BLEU type: bleu value: 67.9 - name: chr-F type: chrf value: 0.82758 - task: name: Translation spa-fra type: translation args: spa-fra dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: spa-fra metrics: - name: BLEU type: bleu value: 57.3 - name: chr-F type: chrf value: 0.73113 - task: name: Translation spa-glg type: translation args: spa-glg dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: spa-glg metrics: - name: BLEU type: bleu value: 63.0 - name: chr-F type: chrf value: 0.77332 - task: name: Translation spa-ita type: translation args: spa-ita dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: spa-ita metrics: - name: BLEU type: bleu value: 60.3 - name: chr-F type: chrf value: 0.77046 - task: name: Translation spa-por type: translation args: spa-por dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: spa-por metrics: - name: BLEU type: bleu value: 59.1 - name: chr-F type: chrf value: 0.75854 - task: name: Translation spa-ron type: translation args: spa-ron dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: spa-ron metrics: - name: BLEU type: bleu value: 45.5 - name: chr-F type: chrf value: 0.66679 - task: name: Translation fra-ita type: translation args: fra-ita dataset: name: newstest2009 type: wmt-2009-news args: fra-ita metrics: - name: BLEU type: bleu value: 31.2 - name: chr-F type: chrf value: 0.59764 - task: name: Translation fra-spa type: translation args: fra-spa dataset: name: newstest2009 type: wmt-2009-news args: fra-spa metrics: - name: BLEU type: bleu value: 32.5 - name: chr-F type: chrf value: 0.58829 - task: name: Translation ita-fra type: translation args: ita-fra dataset: name: newstest2009 type: wmt-2009-news args: ita-fra metrics: - name: BLEU type: bleu value: 31.6 - name: chr-F type: chrf value: 0.59084 - task: name: Translation ita-spa type: translation args: ita-spa dataset: name: newstest2009 type: wmt-2009-news args: ita-spa metrics: - name: BLEU type: bleu value: 33.5 - name: chr-F type: chrf value: 0.59669 - task: name: Translation spa-fra type: translation args: spa-fra dataset: name: newstest2009 type: wmt-2009-news args: spa-fra metrics: - name: BLEU type: bleu value: 32.3 - name: chr-F type: chrf value: 0.59096 - task: name: Translation spa-ita type: translation args: spa-ita dataset: name: newstest2009 type: wmt-2009-news args: spa-ita metrics: - name: BLEU type: bleu value: 33.2 - name: chr-F type: chrf value: 0.60783 - task: name: Translation fra-spa type: translation args: fra-spa dataset: name: newstest2010 type: wmt-2010-news args: fra-spa metrics: - name: BLEU type: bleu value: 37.8 - name: chr-F type: chrf value: 0.62250 - task: name: Translation spa-fra type: translation args: spa-fra dataset: name: newstest2010 type: wmt-2010-news args: spa-fra metrics: - name: BLEU type: bleu value: 36.2 - name: chr-F type: chrf value: 0.61953 - task: name: Translation fra-spa type: translation args: fra-spa dataset: name: newstest2011 type: wmt-2011-news args: fra-spa metrics: - name: BLEU type: bleu value: 39.8 - name: chr-F type: chrf value: 0.62953 - task: name: Translation spa-fra type: translation args: spa-fra dataset: name: newstest2011 type: wmt-2011-news args: spa-fra metrics: - name: BLEU type: bleu value: 34.9 - name: chr-F type: chrf value: 0.61130 - task: name: Translation fra-spa type: translation args: fra-spa dataset: name: newstest2012 type: wmt-2012-news args: fra-spa metrics: - name: BLEU type: bleu value: 39.0 - name: chr-F type: chrf value: 0.62397 - task: name: Translation spa-fra type: translation args: spa-fra dataset: name: newstest2012 type: wmt-2012-news args: spa-fra metrics: - name: BLEU type: bleu value: 34.3 - name: chr-F type: chrf value: 0.60927 - task: name: Translation fra-spa type: translation args: fra-spa dataset: name: newstest2013 type: wmt-2013-news args: fra-spa metrics: - name: BLEU type: bleu value: 34.9 - name: chr-F type: chrf value: 0.59312 - task: name: Translation spa-fra type: translation args: spa-fra dataset: name: newstest2013 type: wmt-2013-news args: spa-fra metrics: - name: BLEU type: bleu value: 33.6 - name: chr-F type: chrf value: 0.59468 - task: name: Translation cat-ita type: translation args: cat-ita dataset: name: wmt21-ml-wp type: wmt21-ml-wp args: cat-ita metrics: - name: BLEU type: bleu value: 47.8 - name: chr-F type: chrf value: 0.69968 - task: name: Translation cat-oci type: translation args: cat-oci dataset: name: wmt21-ml-wp type: wmt21-ml-wp args: cat-oci metrics: - name: BLEU type: bleu value: 51.6 - name: chr-F type: chrf value: 0.73808 - task: name: Translation cat-ron type: translation args: cat-ron dataset: name: wmt21-ml-wp type: wmt21-ml-wp args: cat-ron metrics: - name: BLEU type: bleu value: 29.0 - name: chr-F type: chrf value: 0.51178 - task: name: Translation ita-cat type: translation args: ita-cat dataset: name: wmt21-ml-wp type: wmt21-ml-wp args: ita-cat metrics: - name: BLEU type: bleu value: 48.9 - name: chr-F type: chrf value: 0.70538 - task: name: Translation ita-oci type: translation args: ita-oci dataset: name: wmt21-ml-wp type: wmt21-ml-wp args: ita-oci metrics: - name: BLEU type: bleu value: 32.0 - name: chr-F type: chrf value: 0.59025 - task: name: Translation ita-ron type: translation args: ita-ron dataset: name: wmt21-ml-wp type: wmt21-ml-wp args: ita-ron metrics: - name: BLEU type: bleu value: 28.9 - name: chr-F type: chrf value: 0.51261 - task: name: Translation oci-cat type: translation args: oci-cat dataset: name: wmt21-ml-wp type: wmt21-ml-wp args: oci-cat metrics: - name: BLEU type: bleu value: 66.1 - name: chr-F type: chrf value: 0.80908 - task: name: Translation oci-ita type: translation args: oci-ita dataset: name: wmt21-ml-wp type: wmt21-ml-wp args: oci-ita metrics: - name: BLEU type: bleu value: 39.6 - name: chr-F type: chrf value: 0.63584 - task: name: Translation oci-ron type: translation args: oci-ron dataset: name: wmt21-ml-wp type: wmt21-ml-wp args: oci-ron metrics: - name: BLEU type: bleu value: 24.6 - name: chr-F type: chrf value: 0.47384 - task: name: Translation ron-cat type: translation args: ron-cat dataset: name: wmt21-ml-wp type: wmt21-ml-wp args: ron-cat metrics: - name: BLEU type: bleu value: 31.1 - name: chr-F type: chrf value: 0.52994 - task: name: Translation ron-ita type: translation args: ron-ita dataset: name: wmt21-ml-wp type: wmt21-ml-wp args: ron-ita metrics: - name: BLEU type: bleu value: 29.6 - name: chr-F type: chrf value: 0.52714 - task: name: Translation ron-oci type: translation args: ron-oci dataset: name: wmt21-ml-wp type: wmt21-ml-wp args: ron-oci metrics: - name: BLEU type: bleu value: 21.3 - name: chr-F type: chrf value: 0.45932 --- # opus-mt-tc-big-itc-itc ## Table of Contents - [Model Details](#model-details) - [Uses](#uses) - [Risks, Limitations and Biases](#risks-limitations-and-biases) - [How to Get Started With the Model](#how-to-get-started-with-the-model) - [Training](#training) - [Evaluation](#evaluation) - [Citation Information](#citation-information) - [Acknowledgements](#acknowledgements) ## Model Details Neural machine translation model for translating from Italic languages (itc) to Italic languages (itc). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). **Model Description:** - **Developed by:** Language Technology Research Group at the University of Helsinki - **Model Type:** Translation (transformer-big) - **Release**: 2022-08-10 - **License:** CC-BY-4.0 - **Language(s):** - Source Language(s): ast cat cbk fra fro glg hat ita lad lad_Latn lat lat_Latn lij lld oci pms por ron spa - Target Language(s): ast cat fra gcf glg hat ita lad lad_Latn lat lat_Latn oci por ron spa - Language Pair(s): ast-cat ast-fra ast-glg ast-ita ast-oci ast-por ast-ron ast-spa cat-ast cat-fra cat-glg cat-ita cat-oci cat-por cat-ron cat-spa fra-ast fra-cat fra-glg fra-ita fra-oci fra-por fra-ron fra-spa glg-ast glg-cat glg-fra glg-ita glg-oci glg-por glg-ron glg-spa ita-ast ita-cat ita-fra ita-glg ita-oci ita-por ita-ron ita-spa lad-spa lad_Latn-spa oci-ast oci-cat oci-fra oci-glg oci-ita oci-por oci-ron oci-spa pms-ita por-ast por-cat por-fra por-glg por-ita por-oci por-ron por-spa ron-ast ron-cat ron-fra ron-glg ron-ita ron-oci ron-por ron-spa spa-cat spa-fra spa-glg spa-ita spa-por spa-ron - Valid Target Language Labels: >>acf<< >>aoa<< >>arg<< >>ast<< >>cat<< >>cbk<< >>cbk_Latn<< >>ccd<< >>cks<< >>cos<< >>cri<< >>crs<< >>dlm<< >>drc<< >>egl<< >>ext<< >>fab<< >>fax<< >>fra<< >>frc<< >>frm<< >>frm_Latn<< >>fro<< >>fro_Latn<< >>frp<< >>fur<< >>fur_Latn<< >>gcf<< >>gcf_Latn<< >>gcr<< >>glg<< >>hat<< >>idb<< >>ist<< >>ita<< >>itk<< >>kea<< >>kmv<< >>lad<< >>lad_Latn<< >>lat<< >>lat_Grek<< >>lat_Latn<< >>lij<< >>lld<< >>lld_Latn<< >>lmo<< >>lou<< >>mcm<< >>mfe<< >>mol<< >>mwl<< >>mxi<< >>mzs<< >>nap<< >>nrf<< >>oci<< >>osc<< >>osp<< >>osp_Latn<< >>pap<< >>pcd<< >>pln<< >>pms<< >>pob<< >>por<< >>pov<< >>pre<< >>pro<< >>qbb<< >>qhr<< >>rcf<< >>rgn<< >>roh<< >>ron<< >>ruo<< >>rup<< >>ruq<< >>scf<< >>scn<< >>sdc<< >>sdn<< >>spa<< >>spq<< >>spx<< >>src<< >>srd<< >>sro<< >>tmg<< >>tvy<< >>vec<< >>vkp<< >>wln<< >>xfa<< >>xum<< - **Original Model**: [opusTCv20210807_transformer-big_2022-08-10.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/itc-itc/opusTCv20210807_transformer-big_2022-08-10.zip) - **Resources for more information:** - [OPUS-MT-train GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train) - More information about released models for this language pair: [OPUS-MT itc-itc README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/itc-itc/README.md) - [More information about MarianNMT models in the transformers library](https://huggingface.co/docs/transformers/model_doc/marian) - [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/ This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id<<` (id = valid target language ID), e.g. `>>ast<<` ## Uses This model can be used for translation and text-to-text generation. ## Risks, Limitations and Biases **CONTENT WARNING: Readers should be aware that the model is trained on various public data sets that may contain content that is disturbing, offensive, and can propagate historical and current stereotypes.** Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). ## How to Get Started With the Model A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ ">>fra<< Charras anglés?", ">>fra<< Vull veure't." ] model_name = "pytorch-models/opus-mt-tc-big-itc-itc" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # Conversations anglaises ? # Je veux te voir. ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-itc-itc") print(pipe(">>fra<< Charras anglés?")) # expected output: Conversations anglaises ? ``` ## Training - **Data**: opusTCv20210807 ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) - **Pre-processing**: SentencePiece (spm32k,spm32k) - **Model Type:** transformer-big - **Original MarianNMT Model**: [opusTCv20210807_transformer-big_2022-08-10.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/itc-itc/opusTCv20210807_transformer-big_2022-08-10.zip) - **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train) ## Evaluation * test set translations: [opusTCv20210807_transformer-big_2022-08-10.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/itc-itc/opusTCv20210807_transformer-big_2022-08-10.test.txt) * test set scores: [opusTCv20210807_transformer-big_2022-08-10.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/itc-itc/opusTCv20210807_transformer-big_2022-08-10.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | cat-fra | tatoeba-test-v2021-08-07 | 0.71201 | 54.6 | 700 | 5664 | | cat-ita | tatoeba-test-v2021-08-07 | 0.74198 | 58.4 | 298 | 2028 | | cat-por | tatoeba-test-v2021-08-07 | 0.74930 | 57.4 | 747 | 6119 | | cat-spa | tatoeba-test-v2021-08-07 | 0.87844 | 78.1 | 1534 | 12094 | | fra-cat | tatoeba-test-v2021-08-07 | 0.66525 | 46.2 | 700 | 5342 | | fra-ita | tatoeba-test-v2021-08-07 | 0.72742 | 53.8 | 10091 | 62060 | | fra-por | tatoeba-test-v2021-08-07 | 0.68413 | 48.6 | 10518 | 77650 | | fra-ron | tatoeba-test-v2021-08-07 | 0.65009 | 44.0 | 1925 | 12252 | | fra-spa | tatoeba-test-v2021-08-07 | 0.72080 | 54.8 | 10294 | 78406 | | glg-por | tatoeba-test-v2021-08-07 | 0.76720 | 61.1 | 433 | 3105 | | glg-spa | tatoeba-test-v2021-08-07 | 0.82362 | 71.7 | 2121 | 17443 | | ita-cat | tatoeba-test-v2021-08-07 | 0.72529 | 56.4 | 298 | 2109 | | ita-fra | tatoeba-test-v2021-08-07 | 0.77932 | 65.2 | 10091 | 66377 | | ita-por | tatoeba-test-v2021-08-07 | 0.72798 | 54.0 | 3066 | 25668 | | ita-ron | tatoeba-test-v2021-08-07 | 0.70814 | 51.1 | 1005 | 6209 | | ita-spa | tatoeba-test-v2021-08-07 | 0.77455 | 62.9 | 5000 | 34937 | | lad_Latn-spa | tatoeba-test-v2021-08-07 | 0.59363 | 42.6 | 239 | 1239 | | lad-spa | tatoeba-test-v2021-08-07 | 0.52243 | 34.7 | 276 | 1448 | | oci-fra | tatoeba-test-v2021-08-07 | 0.49660 | 29.6 | 806 | 6302 | | pms-ita | tatoeba-test-v2021-08-07 | 0.40221 | 20.0 | 232 | 1721 | | por-cat | tatoeba-test-v2021-08-07 | 0.71146 | 52.2 | 747 | 6149 | | por-fra | tatoeba-test-v2021-08-07 | 0.75565 | 60.9 | 10518 | 80459 | | por-glg | tatoeba-test-v2021-08-07 | 0.75348 | 59.0 | 433 | 3016 | | por-ita | tatoeba-test-v2021-08-07 | 0.76883 | 58.8 | 3066 | 24897 | | por-ron | tatoeba-test-v2021-08-07 | 0.67838 | 46.6 | 681 | 4521 | | por-spa | tatoeba-test-v2021-08-07 | 0.79336 | 64.8 | 10947 | 87335 | | ron-fra | tatoeba-test-v2021-08-07 | 0.70307 | 55.0 | 1925 | 13347 | | ron-ita | tatoeba-test-v2021-08-07 | 0.73862 | 53.7 | 1005 | 6352 | | ron-por | tatoeba-test-v2021-08-07 | 0.70889 | 50.7 | 681 | 4593 | | ron-spa | tatoeba-test-v2021-08-07 | 0.73529 | 57.2 | 1959 | 12679 | | spa-cat | tatoeba-test-v2021-08-07 | 0.82758 | 67.9 | 1534 | 12343 | | spa-fra | tatoeba-test-v2021-08-07 | 0.73113 | 57.3 | 10294 | 83501 | | spa-glg | tatoeba-test-v2021-08-07 | 0.77332 | 63.0 | 2121 | 16581 | | spa-ita | tatoeba-test-v2021-08-07 | 0.77046 | 60.3 | 5000 | 34515 | | spa-lad_Latn | tatoeba-test-v2021-08-07 | 0.40084 | 14.7 | 239 | 1254 | | spa-por | tatoeba-test-v2021-08-07 | 0.75854 | 59.1 | 10947 | 87610 | | spa-ron | tatoeba-test-v2021-08-07 | 0.66679 | 45.5 | 1959 | 12503 | | ast-cat | flores101-devtest | 0.57870 | 31.8 | 1012 | 27304 | | ast-fra | flores101-devtest | 0.56761 | 31.1 | 1012 | 28343 | | ast-glg | flores101-devtest | 0.55161 | 27.9 | 1012 | 26582 | | ast-ita | flores101-devtest | 0.51764 | 22.1 | 1012 | 27306 | | ast-oci | flores101-devtest | 0.49545 | 20.6 | 1012 | 27305 | | ast-por | flores101-devtest | 0.57347 | 31.5 | 1012 | 26519 | | ast-ron | flores101-devtest | 0.52317 | 24.8 | 1012 | 26799 | | ast-spa | flores101-devtest | 0.49741 | 21.2 | 1012 | 29199 | | cat-ast | flores101-devtest | 0.56754 | 24.7 | 1012 | 24572 | | cat-fra | flores101-devtest | 0.63368 | 38.4 | 1012 | 28343 | | cat-glg | flores101-devtest | 0.59596 | 32.2 | 1012 | 26582 | | cat-ita | flores101-devtest | 0.55886 | 26.3 | 1012 | 27306 | | cat-oci | flores101-devtest | 0.54285 | 24.6 | 1012 | 27305 | | cat-por | flores101-devtest | 0.62913 | 37.7 | 1012 | 26519 | | cat-ron | flores101-devtest | 0.56885 | 29.5 | 1012 | 26799 | | cat-spa | flores101-devtest | 0.53372 | 24.6 | 1012 | 29199 | | fra-ast | flores101-devtest | 0.52696 | 20.7 | 1012 | 24572 | | fra-cat | flores101-devtest | 0.60492 | 34.6 | 1012 | 27304 | | fra-glg | flores101-devtest | 0.57485 | 30.3 | 1012 | 26582 | | fra-ita | flores101-devtest | 0.56493 | 27.3 | 1012 | 27306 | | fra-oci | flores101-devtest | 0.57449 | 28.2 | 1012 | 27305 | | fra-por | flores101-devtest | 0.62211 | 36.9 | 1012 | 26519 | | fra-ron | flores101-devtest | 0.56998 | 29.4 | 1012 | 26799 | | fra-spa | flores101-devtest | 0.52880 | 24.2 | 1012 | 29199 | | glg-ast | flores101-devtest | 0.55090 | 22.4 | 1012 | 24572 | | glg-cat | flores101-devtest | 0.60550 | 32.6 | 1012 | 27304 | | glg-fra | flores101-devtest | 0.62026 | 36.0 | 1012 | 28343 | | glg-ita | flores101-devtest | 0.55834 | 25.9 | 1012 | 27306 | | glg-oci | flores101-devtest | 0.52520 | 21.9 | 1012 | 27305 | | glg-por | flores101-devtest | 0.60027 | 32.7 | 1012 | 26519 | | glg-ron | flores101-devtest | 0.55621 | 27.8 | 1012 | 26799 | | glg-spa | flores101-devtest | 0.53219 | 24.4 | 1012 | 29199 | | ita-ast | flores101-devtest | 0.50741 | 17.1 | 1012 | 24572 | | ita-cat | flores101-devtest | 0.57061 | 27.9 | 1012 | 27304 | | ita-fra | flores101-devtest | 0.60199 | 32.0 | 1012 | 28343 | | ita-glg | flores101-devtest | 0.55312 | 25.9 | 1012 | 26582 | | ita-oci | flores101-devtest | 0.48447 | 18.1 | 1012 | 27305 | | ita-por | flores101-devtest | 0.58162 | 29.0 | 1012 | 26519 | | ita-ron | flores101-devtest | 0.53703 | 24.2 | 1012 | 26799 | | ita-spa | flores101-devtest | 0.52238 | 23.1 | 1012 | 29199 | | oci-ast | flores101-devtest | 0.53010 | 20.2 | 1012 | 24572 | | oci-cat | flores101-devtest | 0.59946 | 32.2 | 1012 | 27304 | | oci-fra | flores101-devtest | 0.64290 | 39.0 | 1012 | 28343 | | oci-glg | flores101-devtest | 0.56737 | 28.0 | 1012 | 26582 | | oci-ita | flores101-devtest | 0.54220 | 24.2 | 1012 | 27306 | | oci-por | flores101-devtest | 0.62127 | 35.7 | 1012 | 26519 | | oci-ron | flores101-devtest | 0.55906 | 28.0 | 1012 | 26799 | | oci-spa | flores101-devtest | 0.52110 | 22.8 | 1012 | 29199 | | por-ast | flores101-devtest | 0.54539 | 22.5 | 1012 | 24572 | | por-cat | flores101-devtest | 0.61809 | 36.4 | 1012 | 27304 | | por-fra | flores101-devtest | 0.64343 | 39.7 | 1012 | 28343 | | por-glg | flores101-devtest | 0.57965 | 30.4 | 1012 | 26582 | | por-ita | flores101-devtest | 0.55841 | 26.3 | 1012 | 27306 | | por-oci | flores101-devtest | 0.54829 | 25.3 | 1012 | 27305 | | por-ron | flores101-devtest | 0.57283 | 29.8 | 1012 | 26799 | | por-spa | flores101-devtest | 0.53513 | 25.2 | 1012 | 29199 | | ron-ast | flores101-devtest | 0.52265 | 20.1 | 1012 | 24572 | | ron-cat | flores101-devtest | 0.59689 | 32.6 | 1012 | 27304 | | ron-fra | flores101-devtest | 0.63060 | 37.4 | 1012 | 28343 | | ron-glg | flores101-devtest | 0.56677 | 29.3 | 1012 | 26582 | | ron-ita | flores101-devtest | 0.55485 | 25.6 | 1012 | 27306 | | ron-oci | flores101-devtest | 0.52433 | 21.8 | 1012 | 27305 | | ron-por | flores101-devtest | 0.61831 | 36.1 | 1012 | 26519 | | ron-spa | flores101-devtest | 0.52712 | 24.1 | 1012 | 29199 | | spa-ast | flores101-devtest | 0.49008 | 15.7 | 1012 | 24572 | | spa-cat | flores101-devtest | 0.53905 | 23.2 | 1012 | 27304 | | spa-fra | flores101-devtest | 0.57078 | 27.4 | 1012 | 28343 | | spa-glg | flores101-devtest | 0.52563 | 22.0 | 1012 | 26582 | | spa-ita | flores101-devtest | 0.52783 | 22.3 | 1012 | 27306 | | spa-oci | flores101-devtest | 0.48064 | 16.3 | 1012 | 27305 | | spa-por | flores101-devtest | 0.55736 | 25.8 | 1012 | 26519 | | spa-ron | flores101-devtest | 0.51623 | 21.4 | 1012 | 26799 | | fra-ita | newssyscomb2009 | 0.60995 | 32.1 | 502 | 11551 | | fra-spa | newssyscomb2009 | 0.60224 | 34.2 | 502 | 12503 | | ita-fra | newssyscomb2009 | 0.61237 | 33.7 | 502 | 12331 | | ita-spa | newssyscomb2009 | 0.60706 | 35.4 | 502 | 12503 | | spa-fra | newssyscomb2009 | 0.61290 | 34.6 | 502 | 12331 | | spa-ita | newssyscomb2009 | 0.61632 | 33.3 | 502 | 11551 | | fra-spa | news-test2008 | 0.58939 | 33.9 | 2051 | 52586 | | spa-fra | news-test2008 | 0.58695 | 32.4 | 2051 | 52685 | | fra-ita | newstest2009 | 0.59764 | 31.2 | 2525 | 63466 | | fra-spa | newstest2009 | 0.58829 | 32.5 | 2525 | 68111 | | ita-fra | newstest2009 | 0.59084 | 31.6 | 2525 | 69263 | | ita-spa | newstest2009 | 0.59669 | 33.5 | 2525 | 68111 | | spa-fra | newstest2009 | 0.59096 | 32.3 | 2525 | 69263 | | spa-ita | newstest2009 | 0.60783 | 33.2 | 2525 | 63466 | | fra-spa | newstest2010 | 0.62250 | 37.8 | 2489 | 65480 | | spa-fra | newstest2010 | 0.61953 | 36.2 | 2489 | 66022 | | fra-spa | newstest2011 | 0.62953 | 39.8 | 3003 | 79476 | | spa-fra | newstest2011 | 0.61130 | 34.9 | 3003 | 80626 | | fra-spa | newstest2012 | 0.62397 | 39.0 | 3003 | 79006 | | spa-fra | newstest2012 | 0.60927 | 34.3 | 3003 | 78011 | | fra-spa | newstest2013 | 0.59312 | 34.9 | 3000 | 70528 | | spa-fra | newstest2013 | 0.59468 | 33.6 | 3000 | 70037 | | cat-ita | wmt21-ml-wp | 0.69968 | 47.8 | 1743 | 42735 | | cat-oci | wmt21-ml-wp | 0.73808 | 51.6 | 1743 | 43736 | | cat-ron | wmt21-ml-wp | 0.51178 | 29.0 | 1743 | 42895 | | ita-cat | wmt21-ml-wp | 0.70538 | 48.9 | 1743 | 43833 | | ita-oci | wmt21-ml-wp | 0.59025 | 32.0 | 1743 | 43736 | | ita-ron | wmt21-ml-wp | 0.51261 | 28.9 | 1743 | 42895 | | oci-cat | wmt21-ml-wp | 0.80908 | 66.1 | 1743 | 43833 | | oci-ita | wmt21-ml-wp | 0.63584 | 39.6 | 1743 | 42735 | | oci-ron | wmt21-ml-wp | 0.47384 | 24.6 | 1743 | 42895 | | ron-cat | wmt21-ml-wp | 0.52994 | 31.1 | 1743 | 43833 | | ron-ita | wmt21-ml-wp | 0.52714 | 29.6 | 1743 | 42735 | | ron-oci | wmt21-ml-wp | 0.45932 | 21.3 | 1743 | 43736 | ## Citation Information * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 8b9f0b0 * port time: Fri Aug 12 23:57:49 EEST 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-lv-en
Helsinki-NLP
2023-10-10T10:55:14Z
175
0
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "en", "lv", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T16:46:59Z
--- language: - en - lv tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-lv-en results: - task: name: Translation lav-eng type: translation args: lav-eng dataset: name: flores101-devtest type: flores_101 args: lav eng devtest metrics: - name: BLEU type: bleu value: 37.2 - task: name: Translation lav-eng type: translation args: lav-eng dataset: name: newsdev2017 type: newsdev2017 args: lav-eng metrics: - name: BLEU type: bleu value: 30.8 - task: name: Translation lav-eng type: translation args: lav-eng dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: lav-eng metrics: - name: BLEU type: bleu value: 59.2 - task: name: Translation lav-eng type: translation args: lav-eng dataset: name: newstest2017 type: wmt-2017-news args: lav-eng metrics: - name: BLEU type: bleu value: 21.8 --- # opus-mt-tc-big-lv-en Neural machine translation model for translating from Latvian (lv) to English (en). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-03-13 * source language(s): lav * target language(s): eng * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-03-13.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/lav-eng/opusTCv20210807+bt_transformer-big_2022-03-13.zip) * more information released models: [OPUS-MT lav-eng README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/lav-eng/README.md) ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ "Dienai ir divdesmit četras stundas.", "Jys lobs advokats." ] model_name = "pytorch-models/opus-mt-tc-big-lv-en" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # The day has twenty-four hours. # Jys lobs lawyer. ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-lv-en") print(pipe("Dienai ir divdesmit četras stundas.")) # expected output: The day has twenty-four hours. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-13.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/lav-eng/opusTCv20210807+bt_transformer-big_2022-03-13.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/lav-eng/opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | lav-eng | tatoeba-test-v2021-08-07 | 0.73884 | 59.2 | 1631 | 11213 | | lav-eng | flores101-devtest | 0.64246 | 37.2 | 1012 | 24721 | | lav-eng | newsdev2017 | 0.55467 | 30.8 | 2003 | 48175 | | lav-eng | newstest2017 | 0.48769 | 21.8 | 2001 | 47511 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 19:46:50 EEST 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-en-et
Helsinki-NLP
2023-10-10T10:54:12Z
114
1
transformers
[ "transformers", "pytorch", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "en", "et", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T14:00:27Z
--- language: - en - et tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-en-et results: - task: name: Translation eng-est type: translation args: eng-est dataset: name: flores101-devtest type: flores_101 args: eng est devtest metrics: - name: BLEU type: bleu value: 28.3 - task: name: Translation eng-est type: translation args: eng-est dataset: name: newsdev2018 type: newsdev2018 args: eng-est metrics: - name: BLEU type: bleu value: 25.2 - task: name: Translation eng-est type: translation args: eng-est dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-est metrics: - name: BLEU type: bleu value: 53.4 - task: name: Translation eng-est type: translation args: eng-est dataset: name: newstest2018 type: wmt-2018-news args: eng-est metrics: - name: BLEU type: bleu value: 26.7 --- # opus-mt-tc-big-en-et Neural machine translation model for translating from English (en) to Estonian (et). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-03-13 * source language(s): eng * target language(s): est * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-03-13.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-est/opusTCv20210807+bt_transformer-big_2022-03-13.zip) * more information released models: [OPUS-MT eng-est README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-est/README.md) ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ ">>est<< A cab is waiting.", ">>vro<< Where do you live?" ] model_name = "pytorch-models/opus-mt-tc-big-en-et" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # Takso ootab. # Kus sa elad? ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-et") print(pipe(">>est<< A cab is waiting.")) # expected output: Takso ootab. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-13.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-est/opusTCv20210807+bt_transformer-big_2022-03-13.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-est/opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | eng-est | tatoeba-test-v2021-08-07 | 0.71255 | 53.4 | 1359 | 7992 | | eng-est | flores101-devtest | 0.61306 | 28.3 | 1012 | 19788 | | eng-est | newsdev2018 | 0.57225 | 25.2 | 2000 | 34492 | | eng-est | newstest2018 | 0.58540 | 26.7 | 2000 | 36269 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 17:00:19 EEST 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-gmq-en
Helsinki-NLP
2023-10-10T10:53:03Z
130
0
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "tc", "big", "gmq", "en", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T16:13:21Z
--- language: - da - en - fo - gmq - is - nb - nn - false - sv tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-gmq-en results: - task: name: Translation dan-eng type: translation args: dan-eng dataset: name: flores101-devtest type: flores_101 args: dan eng devtest metrics: - name: BLEU type: bleu value: 49.3 - task: name: Translation isl-eng type: translation args: isl-eng dataset: name: flores101-devtest type: flores_101 args: isl eng devtest metrics: - name: BLEU type: bleu value: 34.2 - task: name: Translation nob-eng type: translation args: nob-eng dataset: name: flores101-devtest type: flores_101 args: nob eng devtest metrics: - name: BLEU type: bleu value: 44.2 - task: name: Translation swe-eng type: translation args: swe-eng dataset: name: flores101-devtest type: flores_101 args: swe eng devtest metrics: - name: BLEU type: bleu value: 49.8 - task: name: Translation isl-eng type: translation args: isl-eng dataset: name: newsdev2021.is-en type: newsdev2021.is-en args: isl-eng metrics: - name: BLEU type: bleu value: 30.4 - task: name: Translation dan-eng type: translation args: dan-eng dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: dan-eng metrics: - name: BLEU type: bleu value: 65.9 - task: name: Translation fao-eng type: translation args: fao-eng dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: fao-eng metrics: - name: BLEU type: bleu value: 30.1 - task: name: Translation isl-eng type: translation args: isl-eng dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: isl-eng metrics: - name: BLEU type: bleu value: 53.3 - task: name: Translation nno-eng type: translation args: nno-eng dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: nno-eng metrics: - name: BLEU type: bleu value: 56.1 - task: name: Translation nob-eng type: translation args: nob-eng dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: nob-eng metrics: - name: BLEU type: bleu value: 60.2 - task: name: Translation swe-eng type: translation args: swe-eng dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: swe-eng metrics: - name: BLEU type: bleu value: 66.4 - task: name: Translation isl-eng type: translation args: isl-eng dataset: name: newstest2021.is-en type: wmt-2021-news args: isl-eng metrics: - name: BLEU type: bleu value: 34.4 --- # opus-mt-tc-big-gmq-en Neural machine translation model for translating from North Germanic languages (gmq) to English (en). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-03-09 * source language(s): dan fao isl nno nob nor swe * target language(s): eng * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-03-09.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-eng/opusTCv20210807+bt_transformer-big_2022-03-09.zip) * more information released models: [OPUS-MT gmq-eng README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/gmq-eng/README.md) ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ "Han var synligt nervøs.", "Inte ens Tom själv var övertygad." ] model_name = "pytorch-models/opus-mt-tc-big-gmq-en" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # He was visibly nervous. # Even Tom was not convinced. ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-gmq-en") print(pipe("Han var synligt nervøs.")) # expected output: He was visibly nervous. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-09.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-eng/opusTCv20210807+bt_transformer-big_2022-03-09.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-09.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-eng/opusTCv20210807+bt_transformer-big_2022-03-09.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | dan-eng | tatoeba-test-v2021-08-07 | 0.78292 | 65.9 | 10795 | 79684 | | fao-eng | tatoeba-test-v2021-08-07 | 0.47467 | 30.1 | 294 | 1984 | | isl-eng | tatoeba-test-v2021-08-07 | 0.68346 | 53.3 | 2503 | 19788 | | nno-eng | tatoeba-test-v2021-08-07 | 0.69788 | 56.1 | 460 | 3524 | | nob-eng | tatoeba-test-v2021-08-07 | 0.73524 | 60.2 | 4539 | 36823 | | swe-eng | tatoeba-test-v2021-08-07 | 0.77665 | 66.4 | 10362 | 68513 | | dan-eng | flores101-devtest | 0.72322 | 49.3 | 1012 | 24721 | | isl-eng | flores101-devtest | 0.59616 | 34.2 | 1012 | 24721 | | nob-eng | flores101-devtest | 0.68224 | 44.2 | 1012 | 24721 | | swe-eng | flores101-devtest | 0.72042 | 49.8 | 1012 | 24721 | | isl-eng | newsdev2021.is-en | 0.56709 | 30.4 | 2004 | 46383 | | isl-eng | newstest2021.is-en | 0.57756 | 34.4 | 1000 | 22529 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 19:13:11 EEST 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-en-ces_slk
Helsinki-NLP
2023-10-10T10:51:59Z
139
3
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "ces", "slk", "cs", "sk", "en", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T13:46:59Z
--- language: - ces - slk - cs - sk - en tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-en-ces_slk results: - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: flores101-devtest type: flores_101 args: eng ces devtest metrics: - name: BLEU type: bleu value: 34.1 - task: name: Translation eng-slk type: translation args: eng-slk dataset: name: flores101-devtest type: flores_101 args: eng slk devtest metrics: - name: BLEU type: bleu value: 35.9 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: multi30k_test_2016_flickr type: multi30k-2016_flickr args: eng-ces metrics: - name: BLEU type: bleu value: 33.4 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: multi30k_test_2018_flickr type: multi30k-2018_flickr args: eng-ces metrics: - name: BLEU type: bleu value: 33.4 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: news-test2008 type: news-test2008 args: eng-ces metrics: - name: BLEU type: bleu value: 22.8 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-ces metrics: - name: BLEU type: bleu value: 47.5 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: newstest2009 type: wmt-2009-news args: eng-ces metrics: - name: BLEU type: bleu value: 24.3 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: newstest2010 type: wmt-2010-news args: eng-ces metrics: - name: BLEU type: bleu value: 24.4 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: newstest2011 type: wmt-2011-news args: eng-ces metrics: - name: BLEU type: bleu value: 25.5 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: newstest2012 type: wmt-2012-news args: eng-ces metrics: - name: BLEU type: bleu value: 22.6 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: newstest2013 type: wmt-2013-news args: eng-ces metrics: - name: BLEU type: bleu value: 27.4 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: newstest2014 type: wmt-2014-news args: eng-ces metrics: - name: BLEU type: bleu value: 31.4 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: newstest2015 type: wmt-2015-news args: eng-ces metrics: - name: BLEU type: bleu value: 27.0 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: newstest2016 type: wmt-2016-news args: eng-ces metrics: - name: BLEU type: bleu value: 29.9 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: newstest2017 type: wmt-2017-news args: eng-ces metrics: - name: BLEU type: bleu value: 24.9 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: newstest2018 type: wmt-2018-news args: eng-ces metrics: - name: BLEU type: bleu value: 24.6 - task: name: Translation eng-ces type: translation args: eng-ces dataset: name: newstest2019 type: wmt-2019-news args: eng-ces metrics: - name: BLEU type: bleu value: 26.4 --- # opus-mt-tc-big-en-ces_slk Neural machine translation model for translating from English (en) to Czech and Slovak (ces+slk). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-03-13 * source language(s): eng * target language(s): ces * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-03-13.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ces+slk/opusTCv20210807+bt_transformer-big_2022-03-13.zip) * more information released models: [OPUS-MT eng-ces+slk README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-ces+slk/README.md) ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ ">>ces<< We were enemies.", ">>ces<< Do you think Tom knows what's going on?" ] model_name = "pytorch-models/opus-mt-tc-big-en-ces_slk" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # Byli jsme nepřátelé. # Myslíš, že Tom ví, co se děje? ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-ces_slk") print(pipe(">>ces<< We were enemies.")) # expected output: Byli jsme nepřátelé. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-13.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ces+slk/opusTCv20210807+bt_transformer-big_2022-03-13.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ces+slk/opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | eng-ces | tatoeba-test-v2021-08-07 | 0.66128 | 47.5 | 13824 | 91332 | | eng-ces | flores101-devtest | 0.60411 | 34.1 | 1012 | 22101 | | eng-slk | flores101-devtest | 0.62415 | 35.9 | 1012 | 22543 | | eng-ces | multi30k_test_2016_flickr | 0.58547 | 33.4 | 1000 | 10503 | | eng-ces | multi30k_test_2018_flickr | 0.59236 | 33.4 | 1071 | 11631 | | eng-ces | newssyscomb2009 | 0.52702 | 25.3 | 502 | 10032 | | eng-ces | news-test2008 | 0.50286 | 22.8 | 2051 | 42484 | | eng-ces | newstest2009 | 0.52152 | 24.3 | 2525 | 55533 | | eng-ces | newstest2010 | 0.52527 | 24.4 | 2489 | 52955 | | eng-ces | newstest2011 | 0.52721 | 25.5 | 3003 | 65653 | | eng-ces | newstest2012 | 0.50007 | 22.6 | 3003 | 65456 | | eng-ces | newstest2013 | 0.53643 | 27.4 | 3000 | 57250 | | eng-ces | newstest2014 | 0.58944 | 31.4 | 3003 | 59902 | | eng-ces | newstest2015 | 0.55094 | 27.0 | 2656 | 45858 | | eng-ces | newstest2016 | 0.56864 | 29.9 | 2999 | 56998 | | eng-ces | newstest2017 | 0.52504 | 24.9 | 3005 | 54361 | | eng-ces | newstest2018 | 0.52490 | 24.6 | 2983 | 54652 | | eng-ces | newstest2019 | 0.53994 | 26.4 | 1997 | 43113 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 16:46:48 EEST 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-en-lv
Helsinki-NLP
2023-10-10T10:50:52Z
164
0
transformers
[ "transformers", "pytorch", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "en", "lv", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T14:36:12Z
--- language: - en - lv tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-en-lv results: - task: name: Translation eng-lav type: translation args: eng-lav dataset: name: flores101-devtest type: flores_101 args: eng lav devtest metrics: - name: BLEU type: bleu value: 30.1 - task: name: Translation eng-lav type: translation args: eng-lav dataset: name: newsdev2017 type: newsdev2017 args: eng-lav metrics: - name: BLEU type: bleu value: 28.9 - task: name: Translation eng-lav type: translation args: eng-lav dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-lav metrics: - name: BLEU type: bleu value: 44.0 - task: name: Translation eng-lav type: translation args: eng-lav dataset: name: newstest2017 type: wmt-2017-news args: eng-lav metrics: - name: BLEU type: bleu value: 22.1 --- # opus-mt-tc-big-en-lv Neural machine translation model for translating from English (en) to Latvian (lv). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-03-13 * source language(s): eng * target language(s): lav * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-03-13.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-lav/opusTCv20210807+bt_transformer-big_2022-03-13.zip) * more information released models: [OPUS-MT eng-lav README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-lav/README.md) ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ ">>lav<< A day has twenty-four hours.", ">>ltg<< He's a good lawyer." ] model_name = "pytorch-models/opus-mt-tc-big-en-lv" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # Dienā ir divdesmit četras stundas. # Vyss ir labs advokats. ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-lv") print(pipe(">>lav<< A day has twenty-four hours.")) # expected output: Dienā ir divdesmit četras stundas. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-13.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-lav/opusTCv20210807+bt_transformer-big_2022-03-13.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-lav/opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | eng-lav | tatoeba-test-v2021-08-07 | 0.66411 | 44.0 | 1631 | 9932 | | eng-lav | flores101-devtest | 0.59397 | 30.1 | 1012 | 22092 | | eng-lav | newsdev2017 | 0.58082 | 28.9 | 2003 | 41503 | | eng-lav | newstest2017 | 0.53202 | 22.1 | 2001 | 39392 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 17:36:04 EEST 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-bg-en
Helsinki-NLP
2023-10-10T10:49:48Z
170
2
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "bg", "en", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T15:24:05Z
--- language: - bg - en tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-bg-en results: - task: name: Translation bul-eng type: translation args: bul-eng dataset: name: flores101-devtest type: flores_101 args: bul eng devtest metrics: - name: BLEU type: bleu value: 42.9 - task: name: Translation bul-eng type: translation args: bul-eng dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: bul-eng metrics: - name: BLEU type: bleu value: 60.5 --- # opus-mt-tc-big-bg-en Neural machine translation model for translating from Bulgarian (bg) to English (en). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-03-09 * source language(s): bul * target language(s): eng * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-03-09.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-eng/opusTCv20210807+bt_transformer-big_2022-03-09.zip) * more information released models: [OPUS-MT bul-eng README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-eng/README.md) ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ "2001 е годината, с която започва 21-ви век.", "Това е Copacabana!" ] model_name = "pytorch-models/opus-mt-tc-big-bg-en" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # 2001 was the year the 21st century began. # It's Copacabana! ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-bg-en") print(pipe("2001 е годината, с която започва 21-ви век.")) # expected output: 2001 was the year the 21st century began. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-09.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-eng/opusTCv20210807+bt_transformer-big_2022-03-09.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-09.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-eng/opusTCv20210807+bt_transformer-big_2022-03-09.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | bul-eng | tatoeba-test-v2021-08-07 | 0.73687 | 60.5 | 10000 | 71872 | | bul-eng | flores101-devtest | 0.67938 | 42.9 | 1012 | 24721 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 18:23:56 EEST 2022 * port machine: LM0-400-22516.local
twdent/segformer-b5-finetuned-Hiking
twdent
2023-10-10T10:47:18Z
192
0
transformers
[ "transformers", "pytorch", "segformer", "vision", "image-segmentation", "generated_from_trainer", "base_model:nvidia/mit-b5", "base_model:finetune:nvidia/mit-b5", "license:other", "endpoints_compatible", "region:us" ]
image-segmentation
2023-10-10T10:34:13Z
--- license: other base_model: nvidia/mit-b5 tags: - vision - image-segmentation - generated_from_trainer model-index: - name: segformer-b5-finetuned-Hiking results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b5-finetuned-Hiking This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the twdent/Hiking dataset. It achieves the following results on the evaluation set: - Loss: 0.1401 - Mean Iou: 0.6237 - Mean Accuracy: 0.9673 - Overall Accuracy: 0.9683 - Accuracy Unlabeled: nan - Accuracy Traversable: 0.9641 - Accuracy Non-traversable: 0.9705 - Iou Unlabeled: 0.0 - Iou Traversable: 0.9178 - Iou Non-traversable: 0.9532 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 6e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Traversable | Accuracy Non-traversable | Iou Unlabeled | Iou Traversable | Iou Non-traversable | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------------:|:------------------------:|:-------------:|:---------------:|:-------------------:| | 0.2675 | 1.33 | 20 | 0.2742 | 0.6058 | 0.9616 | 0.9550 | nan | 0.9826 | 0.9406 | 0.0 | 0.8853 | 0.9321 | | 0.1418 | 2.67 | 40 | 0.1827 | 0.6073 | 0.9562 | 0.9566 | nan | 0.9548 | 0.9575 | 0.0 | 0.8858 | 0.9360 | | 0.0949 | 4.0 | 60 | 0.1561 | 0.6002 | 0.9382 | 0.9523 | nan | 0.8931 | 0.9832 | 0.0 | 0.8692 | 0.9314 | | 0.0684 | 5.33 | 80 | 0.1364 | 0.6135 | 0.9556 | 0.9614 | nan | 0.9369 | 0.9742 | 0.0 | 0.8967 | 0.9437 | | 0.0627 | 6.67 | 100 | 0.1289 | 0.6122 | 0.9506 | 0.9610 | nan | 0.9177 | 0.9836 | 0.0 | 0.8928 | 0.9438 | | 0.0625 | 8.0 | 120 | 0.1097 | 0.6208 | 0.9610 | 0.9658 | nan | 0.9458 | 0.9762 | 0.0 | 0.9113 | 0.9510 | | 0.0371 | 9.33 | 140 | 0.1361 | 0.6130 | 0.9551 | 0.9610 | nan | 0.9361 | 0.9741 | 0.0 | 0.8959 | 0.9431 | | 0.0409 | 10.67 | 160 | 0.1239 | 0.6194 | 0.9615 | 0.9653 | nan | 0.9494 | 0.9737 | 0.0 | 0.9086 | 0.9494 | | 0.0457 | 12.0 | 180 | 0.0993 | 0.6281 | 0.9715 | 0.9713 | nan | 0.9723 | 0.9707 | 0.0 | 0.9264 | 0.9579 | | 0.0368 | 13.33 | 200 | 0.1354 | 0.6146 | 0.9563 | 0.9617 | nan | 0.9389 | 0.9737 | 0.0 | 0.8993 | 0.9446 | | 0.0667 | 14.67 | 220 | 0.1208 | 0.6171 | 0.9565 | 0.9644 | nan | 0.9316 | 0.9815 | 0.0 | 0.9032 | 0.9482 | | 0.029 | 16.0 | 240 | 0.0946 | 0.6291 | 0.9695 | 0.9724 | nan | 0.9606 | 0.9785 | 0.0 | 0.9276 | 0.9596 | | 0.0467 | 17.33 | 260 | 0.1188 | 0.6224 | 0.9655 | 0.9676 | nan | 0.9589 | 0.9721 | 0.0 | 0.9151 | 0.9522 | | 0.0449 | 18.67 | 280 | 0.1201 | 0.6212 | 0.9638 | 0.9667 | nan | 0.9545 | 0.9731 | 0.0 | 0.9125 | 0.9511 | | 0.0353 | 20.0 | 300 | 0.1285 | 0.6234 | 0.9687 | 0.9681 | nan | 0.9706 | 0.9668 | 0.0 | 0.9174 | 0.9527 | | 0.025 | 21.33 | 320 | 0.1292 | 0.6204 | 0.9641 | 0.9659 | nan | 0.9582 | 0.9699 | 0.0 | 0.9114 | 0.9500 | | 0.0244 | 22.67 | 340 | 0.1352 | 0.6208 | 0.9665 | 0.9664 | nan | 0.9667 | 0.9662 | 0.0 | 0.9124 | 0.9501 | | 0.035 | 24.0 | 360 | 0.1260 | 0.6252 | 0.9699 | 0.9693 | nan | 0.9718 | 0.9681 | 0.0 | 0.9211 | 0.9544 | | 0.0295 | 25.33 | 380 | 0.1190 | 0.6244 | 0.9669 | 0.9688 | nan | 0.9607 | 0.9730 | 0.0 | 0.9190 | 0.9543 | | 0.032 | 26.67 | 400 | 0.1258 | 0.6253 | 0.9694 | 0.9695 | nan | 0.9693 | 0.9695 | 0.0 | 0.9211 | 0.9547 | | 0.0241 | 28.0 | 420 | 0.1255 | 0.6230 | 0.9658 | 0.9678 | nan | 0.9593 | 0.9723 | 0.0 | 0.9164 | 0.9527 | | 0.0246 | 29.33 | 440 | 0.1273 | 0.6238 | 0.9675 | 0.9683 | nan | 0.9651 | 0.9699 | 0.0 | 0.9179 | 0.9534 | | 0.0214 | 30.67 | 460 | 0.1321 | 0.6233 | 0.9670 | 0.9675 | nan | 0.9652 | 0.9687 | 0.0 | 0.9171 | 0.9527 | | 0.0236 | 32.0 | 480 | 0.1289 | 0.6241 | 0.9687 | 0.9685 | nan | 0.9695 | 0.9679 | 0.0 | 0.9189 | 0.9534 | | 0.0238 | 33.33 | 500 | 0.1309 | 0.6234 | 0.9664 | 0.9680 | nan | 0.9612 | 0.9716 | 0.0 | 0.9172 | 0.9529 | | 0.0204 | 34.67 | 520 | 0.1271 | 0.6249 | 0.9681 | 0.9693 | nan | 0.9643 | 0.9719 | 0.0 | 0.9201 | 0.9547 | | 0.0243 | 36.0 | 540 | 0.1264 | 0.6248 | 0.9679 | 0.9693 | nan | 0.9636 | 0.9723 | 0.0 | 0.9196 | 0.9547 | | 0.0259 | 37.33 | 560 | 0.1305 | 0.6226 | 0.9656 | 0.9679 | nan | 0.9582 | 0.9730 | 0.0 | 0.9154 | 0.9525 | | 0.0341 | 38.67 | 580 | 0.1277 | 0.6245 | 0.9674 | 0.9690 | nan | 0.9623 | 0.9725 | 0.0 | 0.9192 | 0.9543 | | 0.0275 | 40.0 | 600 | 0.1369 | 0.6221 | 0.9653 | 0.9672 | nan | 0.9590 | 0.9715 | 0.0 | 0.9147 | 0.9516 | | 0.0303 | 41.33 | 620 | 0.1380 | 0.6235 | 0.9674 | 0.9681 | nan | 0.9650 | 0.9698 | 0.0 | 0.9175 | 0.9530 | | 0.0207 | 42.67 | 640 | 0.1389 | 0.6237 | 0.9677 | 0.9682 | nan | 0.9662 | 0.9692 | 0.0 | 0.9180 | 0.9531 | | 0.0231 | 44.0 | 660 | 0.1369 | 0.6243 | 0.9679 | 0.9688 | nan | 0.9652 | 0.9707 | 0.0 | 0.9190 | 0.9538 | | 0.0249 | 45.33 | 680 | 0.1379 | 0.6237 | 0.9672 | 0.9683 | nan | 0.9640 | 0.9705 | 0.0 | 0.9179 | 0.9532 | | 0.0382 | 46.67 | 700 | 0.1384 | 0.6239 | 0.9677 | 0.9685 | nan | 0.9650 | 0.9704 | 0.0 | 0.9182 | 0.9534 | | 0.0238 | 48.0 | 720 | 0.1420 | 0.6230 | 0.9668 | 0.9677 | nan | 0.9640 | 0.9697 | 0.0 | 0.9166 | 0.9524 | | 0.0212 | 49.33 | 740 | 0.1401 | 0.6237 | 0.9673 | 0.9683 | nan | 0.9641 | 0.9705 | 0.0 | 0.9178 | 0.9532 | ### Framework versions - Transformers 4.35.0.dev0 - Pytorch 2.1.0+cu118 - Datasets 2.14.5 - Tokenizers 0.14.0
Helsinki-NLP/opus-mt-tc-big-en-ro
Helsinki-NLP
2023-10-10T10:46:29Z
256
4
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "en", "ro", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T14:55:54Z
--- language: - en - ro tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-en-ro results: - task: name: Translation eng-ron type: translation args: eng-ron dataset: name: flores101-devtest type: flores_101 args: eng ron devtest metrics: - name: BLEU type: bleu value: 40.4 - task: name: Translation eng-ron type: translation args: eng-ron dataset: name: newsdev2016 type: newsdev2016 args: eng-ron metrics: - name: BLEU type: bleu value: 36.4 - task: name: Translation eng-ron type: translation args: eng-ron dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-ron metrics: - name: BLEU type: bleu value: 48.6 - task: name: Translation eng-ron type: translation args: eng-ron dataset: name: newstest2016 type: wmt-2016-news args: eng-ron metrics: - name: BLEU type: bleu value: 34.0 --- # opus-mt-tc-big-en-ro Neural machine translation model for translating from English (en) to Romanian (ro). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-02-25 * source language(s): eng * target language(s): ron * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-02-25.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ron/opusTCv20210807+bt_transformer-big_2022-02-25.zip) * more information released models: [OPUS-MT eng-ron README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-ron/README.md) ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ ">>ron<< A bad writer's prose is full of hackneyed phrases.", ">>ron<< Zero is a special number." ] model_name = "pytorch-models/opus-mt-tc-big-en-ro" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # Proza unui scriitor prost este plină de fraze tocite. # Zero este un număr special. ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-ro") print(pipe(">>ron<< A bad writer's prose is full of hackneyed phrases.")) # expected output: Proza unui scriitor prost este plină de fraze tocite. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-02-25.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ron/opusTCv20210807+bt_transformer-big_2022-02-25.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-02-25.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ron/opusTCv20210807+bt_transformer-big_2022-02-25.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | eng-ron | tatoeba-test-v2021-08-07 | 0.68606 | 48.6 | 5508 | 40367 | | eng-ron | flores101-devtest | 0.64876 | 40.4 | 1012 | 26799 | | eng-ron | newsdev2016 | 0.62682 | 36.4 | 1999 | 51300 | | eng-ron | newstest2016 | 0.60702 | 34.0 | 1999 | 48945 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 17:55:46 EEST 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-en-lt
Helsinki-NLP
2023-10-10T10:42:32Z
270
2
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "en", "lt", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T14:42:47Z
--- language: - en - lt tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-en-lt results: - task: name: Translation eng-lit type: translation args: eng-lit dataset: name: flores101-devtest type: flores_101 args: eng lit devtest metrics: - name: BLEU type: bleu value: 28.0 - task: name: Translation eng-lit type: translation args: eng-lit dataset: name: newsdev2019 type: newsdev2019 args: eng-lit metrics: - name: BLEU type: bleu value: 26.6 - task: name: Translation eng-lit type: translation args: eng-lit dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-lit metrics: - name: BLEU type: bleu value: 39.5 - task: name: Translation eng-lit type: translation args: eng-lit dataset: name: newstest2019 type: wmt-2019-news args: eng-lit metrics: - name: BLEU type: bleu value: 17.5 --- # opus-mt-tc-big-en-lt Neural machine translation model for translating from English (en) to Lithuanian (lt). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-02-25 * source language(s): eng * target language(s): lit * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-02-25.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-lit/opusTCv20210807+bt_transformer-big_2022-02-25.zip) * more information released models: [OPUS-MT eng-lit README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-lit/README.md) ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ "A cat was sitting on the chair.", "Yukiko likes potatoes." ] model_name = "pytorch-models/opus-mt-tc-big-en-lt" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # Katė sėdėjo ant kėdės. # Jukiko mėgsta bulves. ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-lt") print(pipe("A cat was sitting on the chair.")) # expected output: Katė sėdėjo ant kėdės. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-02-25.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-lit/opusTCv20210807+bt_transformer-big_2022-02-25.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-02-25.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-lit/opusTCv20210807+bt_transformer-big_2022-02-25.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | eng-lit | tatoeba-test-v2021-08-07 | 0.67434 | 39.5 | 2528 | 14942 | | eng-lit | flores101-devtest | 0.59593 | 28.0 | 1012 | 20695 | | eng-lit | newsdev2019 | 0.58444 | 26.6 | 2000 | 39627 | | eng-lit | newstest2019 | 0.51559 | 17.5 | 998 | 19711 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 17:42:39 EEST 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-en-hu
Helsinki-NLP
2023-10-10T10:40:26Z
1,246
2
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "en", "hu", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T14:21:29Z
--- language: - en - hu tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-en-hu results: - task: name: Translation eng-hun type: translation args: eng-hun dataset: name: flores101-devtest type: flores_101 args: eng hun devtest metrics: - name: BLEU type: bleu value: 29.6 - task: name: Translation eng-hun type: translation args: eng-hun dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-hun metrics: - name: BLEU type: bleu value: 38.7 - task: name: Translation eng-hun type: translation args: eng-hun dataset: name: newstest2009 type: wmt-2009-news args: eng-hun metrics: - name: BLEU type: bleu value: 20.3 --- # opus-mt-tc-big-en-hu Neural machine translation model for translating from English (en) to Hungarian (hu). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-02-25 * source language(s): eng * target language(s): hun * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-02-25.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-hun/opusTCv20210807+bt_transformer-big_2022-02-25.zip) * more information released models: [OPUS-MT eng-hun README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-hun/README.md) ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ "I wish I hadn't seen such a horrible film.", "She's at school." ] model_name = "pytorch-models/opus-mt-tc-big-en-hu" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # Bárcsak ne láttam volna ilyen szörnyű filmet. # Iskolában van. ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-hu") print(pipe("I wish I hadn't seen such a horrible film.")) # expected output: Bárcsak ne láttam volna ilyen szörnyű filmet. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-02-25.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-hun/opusTCv20210807+bt_transformer-big_2022-02-25.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-02-25.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-hun/opusTCv20210807+bt_transformer-big_2022-02-25.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | eng-hun | tatoeba-test-v2021-08-07 | 0.62096 | 38.7 | 13037 | 79562 | | eng-hun | flores101-devtest | 0.60159 | 29.6 | 1012 | 22183 | | eng-hun | newssyscomb2009 | 0.51918 | 20.6 | 502 | 9733 | | eng-hun | newstest2009 | 0.50973 | 20.3 | 2525 | 54965 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 17:21:20 EEST 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-en-zle
Helsinki-NLP
2023-10-10T10:39:20Z
140
0
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "be", "en", "ru", "uk", "zle", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-03-24T12:23:34Z
--- language: - be - en - ru - uk - zle tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-en-zle results: - task: name: Translation eng-rus type: translation args: eng-rus dataset: name: flores101-devtest type: flores_101 args: eng rus devtest metrics: - name: BLEU type: bleu value: 32.7 - task: name: Translation eng-ukr type: translation args: eng-ukr dataset: name: flores101-devtest type: flores_101 args: eng ukr devtest metrics: - name: BLEU type: bleu value: 32.1 - task: name: Translation eng-bel type: translation args: eng-bel dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-bel metrics: - name: BLEU type: bleu value: 24.9 - task: name: Translation eng-rus type: translation args: eng-rus dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-rus metrics: - name: BLEU type: bleu value: 45.5 - task: name: Translation eng-ukr type: translation args: eng-ukr dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-ukr metrics: - name: BLEU type: bleu value: 37.7 - task: name: Translation eng-rus type: translation args: eng-rus dataset: name: tico19-test type: tico19-test args: eng-rus metrics: - name: BLEU type: bleu value: 33.7 - task: name: Translation eng-rus type: translation args: eng-rus dataset: name: newstest2012 type: wmt-2012-news args: eng-rus metrics: - name: BLEU type: bleu value: 36.8 - task: name: Translation eng-rus type: translation args: eng-rus dataset: name: newstest2013 type: wmt-2013-news args: eng-rus metrics: - name: BLEU type: bleu value: 26.9 - task: name: Translation eng-rus type: translation args: eng-rus dataset: name: newstest2014 type: wmt-2014-news args: eng-rus metrics: - name: BLEU type: bleu value: 43.5 - task: name: Translation eng-rus type: translation args: eng-rus dataset: name: newstest2015 type: wmt-2015-news args: eng-rus metrics: - name: BLEU type: bleu value: 34.9 - task: name: Translation eng-rus type: translation args: eng-rus dataset: name: newstest2016 type: wmt-2016-news args: eng-rus metrics: - name: BLEU type: bleu value: 33.1 - task: name: Translation eng-rus type: translation args: eng-rus dataset: name: newstest2017 type: wmt-2017-news args: eng-rus metrics: - name: BLEU type: bleu value: 37.3 - task: name: Translation eng-rus type: translation args: eng-rus dataset: name: newstest2018 type: wmt-2018-news args: eng-rus metrics: - name: BLEU type: bleu value: 32.9 - task: name: Translation eng-rus type: translation args: eng-rus dataset: name: newstest2019 type: wmt-2019-news args: eng-rus metrics: - name: BLEU type: bleu value: 31.8 - task: name: Translation eng-rus type: translation args: eng-rus dataset: name: newstest2020 type: wmt-2020-news args: eng-rus metrics: - name: BLEU type: bleu value: 25.5 --- # opus-mt-tc-big-en-zle Neural machine translation model for translating from English (en) to East Slavic languages (zle). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-03-13 * source language(s): eng * target language(s): bel rus ukr * valid target language labels: >>bel<< >>rus<< >>ukr<< * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-03-13.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-zle/opusTCv20210807+bt_transformer-big_2022-03-13.zip) * more information released models: [OPUS-MT eng-zle README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-zle/README.md) * more information about the model: [MarianMT](https://huggingface.co/docs/transformers/model_doc/marian) This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id<<` (id = valid target language ID), e.g. `>>bel<<` ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ ">>rus<< Are they coming as well?", ">>rus<< I didn't let Tom do what he wanted to do." ] model_name = "pytorch-models/opus-mt-tc-big-en-zle" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # Они тоже приедут? # Я не позволил Тому сделать то, что он хотел. ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-zle") print(pipe(">>rus<< Are they coming as well?")) # expected output: Они тоже приедут? ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-13.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-zle/opusTCv20210807+bt_transformer-big_2022-03-13.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-zle/opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | eng-bel | tatoeba-test-v2021-08-07 | 0.50345 | 24.9 | 2500 | 16237 | | eng-rus | tatoeba-test-v2021-08-07 | 0.66182 | 45.5 | 19425 | 134296 | | eng-ukr | tatoeba-test-v2021-08-07 | 0.60175 | 37.7 | 13127 | 80998 | | eng-bel | flores101-devtest | 0.42078 | 11.2 | 1012 | 24829 | | eng-rus | flores101-devtest | 0.59654 | 32.7 | 1012 | 23295 | | eng-ukr | flores101-devtest | 0.60131 | 32.1 | 1012 | 22810 | | eng-rus | newstest2012 | 0.62842 | 36.8 | 3003 | 64790 | | eng-rus | newstest2013 | 0.54627 | 26.9 | 3000 | 58560 | | eng-rus | newstest2014 | 0.68348 | 43.5 | 3003 | 61603 | | eng-rus | newstest2015 | 0.62621 | 34.9 | 2818 | 55915 | | eng-rus | newstest2016 | 0.60595 | 33.1 | 2998 | 62014 | | eng-rus | newstest2017 | 0.64249 | 37.3 | 3001 | 60253 | | eng-rus | newstest2018 | 0.61219 | 32.9 | 3000 | 61907 | | eng-rus | newstest2019 | 0.57902 | 31.8 | 1997 | 48147 | | eng-rus | newstest2020 | 0.52939 | 25.5 | 2002 | 47083 | | eng-rus | tico19-test | 0.59314 | 33.7 | 2100 | 55843 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 1bdabf7 * port time: Thu Mar 24 01:58:40 EET 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-et-en
Helsinki-NLP
2023-10-10T10:35:11Z
142
0
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "en", "et", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T15:54:21Z
--- language: - en - et tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-et-en results: - task: name: Translation est-eng type: translation args: est-eng dataset: name: flores101-devtest type: flores_101 args: est eng devtest metrics: - name: BLEU type: bleu value: 38.6 - task: name: Translation est-eng type: translation args: est-eng dataset: name: newsdev2018 type: newsdev2018 args: est-eng metrics: - name: BLEU type: bleu value: 33.8 - task: name: Translation est-eng type: translation args: est-eng dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: est-eng metrics: - name: BLEU type: bleu value: 59.7 - task: name: Translation est-eng type: translation args: est-eng dataset: name: newstest2018 type: wmt-2018-news args: est-eng metrics: - name: BLEU type: bleu value: 34.3 --- # opus-mt-tc-big-et-en Neural machine translation model for translating from Estonian (et) to English (en). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-03-09 * source language(s): est * target language(s): eng * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-03-09.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/est-eng/opusTCv20210807+bt_transformer-big_2022-03-09.zip) * more information released models: [OPUS-MT est-eng README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/est-eng/README.md) ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ "Takso ootab.", "Kon sa elät?" ] model_name = "pytorch-models/opus-mt-tc-big-et-en" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # Taxi's waiting. # Kon you elät? ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-et-en") print(pipe("Takso ootab.")) # expected output: Taxi's waiting. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-09.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/est-eng/opusTCv20210807+bt_transformer-big_2022-03-09.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-09.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/est-eng/opusTCv20210807+bt_transformer-big_2022-03-09.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | est-eng | tatoeba-test-v2021-08-07 | 0.73707 | 59.7 | 1359 | 8811 | | est-eng | flores101-devtest | 0.64463 | 38.6 | 1012 | 24721 | | est-eng | newsdev2018 | 0.59899 | 33.8 | 2000 | 43068 | | est-eng | newstest2018 | 0.60708 | 34.3 | 2000 | 45405 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 18:54:11 EEST 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-en-gmq
Helsinki-NLP
2023-10-10T10:34:07Z
3,092
3
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "tc", "big", "en", "gmq", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T14:14:55Z
--- language: - da - en - fo - gmq - is - nb - nn - false - sv tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-en-gmq results: - task: name: Translation eng-dan type: translation args: eng-dan dataset: name: flores101-devtest type: flores_101 args: eng dan devtest metrics: - name: BLEU type: bleu value: 47.7 - task: name: Translation eng-isl type: translation args: eng-isl dataset: name: flores101-devtest type: flores_101 args: eng isl devtest metrics: - name: BLEU type: bleu value: 24.1 - task: name: Translation eng-nob type: translation args: eng-nob dataset: name: flores101-devtest type: flores_101 args: eng nob devtest metrics: - name: BLEU type: bleu value: 34.5 - task: name: Translation eng-swe type: translation args: eng-swe dataset: name: flores101-devtest type: flores_101 args: eng swe devtest metrics: - name: BLEU type: bleu value: 46.9 - task: name: Translation eng-isl type: translation args: eng-isl dataset: name: newsdev2021.en-is type: newsdev2021.en-is args: eng-isl metrics: - name: BLEU type: bleu value: 22.6 - task: name: Translation eng-dan type: translation args: eng-dan dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-dan metrics: - name: BLEU type: bleu value: 61.6 - task: name: Translation eng-isl type: translation args: eng-isl dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-isl metrics: - name: BLEU type: bleu value: 39.9 - task: name: Translation eng-nno type: translation args: eng-nno dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-nno metrics: - name: BLEU type: bleu value: 40.1 - task: name: Translation eng-nob type: translation args: eng-nob dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-nob metrics: - name: BLEU type: bleu value: 57.3 - task: name: Translation eng-swe type: translation args: eng-swe dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-swe metrics: - name: BLEU type: bleu value: 60.9 - task: name: Translation eng-isl type: translation args: eng-isl dataset: name: newstest2021.en-is type: wmt-2021-news args: eng-isl metrics: - name: BLEU type: bleu value: 21.5 --- # opus-mt-tc-big-en-gmq Neural machine translation model for translating from English (en) to North Germanic languages (gmq). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-03-17 * source language(s): eng * target language(s): dan fao isl nno nob nor swe * valid target language labels: >>dan<< >>fao<< >>isl<< >>nno<< >>nob<< >>nor<< >>swe<< * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-03-17.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-gmq/opusTCv20210807+bt_transformer-big_2022-03-17.zip) * more information released models: [OPUS-MT eng-gmq README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-gmq/README.md) * more information about the model: [MarianMT](https://huggingface.co/docs/transformers/model_doc/marian) This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id<<` (id = valid target language ID), e.g. `>>dan<<` ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ ">>nno<< The United States borders Canada.", ">>nob<< This is the biggest hotel in this city." ] model_name = "pytorch-models/opus-mt-tc-big-en-gmq" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # USA grensar til Canada. # Dette er det største hotellet i denne byen. ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-gmq") print(pipe(">>nno<< The United States borders Canada.")) # expected output: USA grensar til Canada. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-17.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-gmq/opusTCv20210807+bt_transformer-big_2022-03-17.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-17.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-gmq/opusTCv20210807+bt_transformer-big_2022-03-17.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | eng-dan | tatoeba-test-v2021-08-07 | 0.75165 | 61.6 | 10795 | 79385 | | eng-fao | tatoeba-test-v2021-08-07 | 0.40395 | 18.3 | 294 | 1933 | | eng-isl | tatoeba-test-v2021-08-07 | 0.59731 | 39.9 | 2503 | 19023 | | eng-nno | tatoeba-test-v2021-08-07 | 0.61271 | 40.1 | 460 | 3428 | | eng-nob | tatoeba-test-v2021-08-07 | 0.72380 | 57.3 | 4539 | 36119 | | eng-swe | tatoeba-test-v2021-08-07 | 0.74197 | 60.9 | 10362 | 68067 | | eng-dan | flores101-devtest | 0.70810 | 47.7 | 1012 | 24638 | | eng-isl | flores101-devtest | 0.52076 | 24.1 | 1012 | 22834 | | eng-nob | flores101-devtest | 0.62760 | 34.5 | 1012 | 23873 | | eng-swe | flores101-devtest | 0.70129 | 46.9 | 1012 | 23121 | | eng-isl | newsdev2021.en-is | 0.50376 | 22.6 | 2004 | 43721 | | eng-isl | newstest2021.en-is | 0.50516 | 21.5 | 1000 | 25233 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 17:14:46 EEST 2022 * port machine: LM0-400-22516.local
YuZhong-Chen/Taxi-v3
YuZhong-Chen
2023-10-10T10:34:03Z
0
0
null
[ "Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T10:34:01Z
--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: Taxi-v3 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 metrics: - type: mean_reward value: 7.50 +/- 2.73 name: mean_reward verified: false --- # **Q-Learning** Agent playing1 **Taxi-v3** This is a trained model of a **Q-Learning** agent playing **Taxi-v3** . ## Usage ```python model = load_from_hub(repo_id="YuZhong-Chen/Taxi-v3", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
YuZhong-Chen/q-FrozenLake-v1-4x4-noSlippery
YuZhong-Chen
2023-10-10T10:32:14Z
0
0
null
[ "FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T10:32:11Z
--- tags: - FrozenLake-v1-4x4-no_slippery - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-FrozenLake-v1-4x4-noSlippery results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: FrozenLake-v1-4x4-no_slippery type: FrozenLake-v1-4x4-no_slippery metrics: - type: mean_reward value: 1.00 +/- 0.00 name: mean_reward verified: false --- # **Q-Learning** Agent playing1 **FrozenLake-v1** This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** . ## Usage ```python model = load_from_hub(repo_id="YuZhong-Chen/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
vardhanam/face
vardhanam
2023-10-10T10:31:26Z
1
0
diffusers
[ "diffusers", "text-to-image", "autotrain", "base_model:stabilityai/stable-diffusion-xl-base-1.0", "base_model:finetune:stabilityai/stable-diffusion-xl-base-1.0", "region:us" ]
text-to-image
2023-10-10T10:31:06Z
--- base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: photo of a vardhanam's face tags: - text-to-image - diffusers - autotrain inference: true --- # DreamBooth trained by AutoTrain Text encoder was not trained.
Helsinki-NLP/opus-mt-tc-big-en-ko
Helsinki-NLP
2023-10-10T10:29:58Z
1,276
14
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "en", "ko", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-08-12T08:02:12Z
--- language: - en - ko tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-en-ko results: - task: name: Translation eng-kor type: translation args: eng-kor dataset: name: flores101-devtest type: flores_101 args: eng kor devtest metrics: - name: BLEU type: bleu value: 13.7 - name: chr-F type: chrf value: 0.36399 --- # opus-mt-tc-big-en-ko ## Table of Contents - [Model Details](#model-details) - [Uses](#uses) - [Risks, Limitations and Biases](#risks-limitations-and-biases) - [How to Get Started With the Model](#how-to-get-started-with-the-model) - [Training](#training) - [Evaluation](#evaluation) - [Citation Information](#citation-information) - [Acknowledgements](#acknowledgements) ## Model Details Neural machine translation model for translating from English (en) to Korean (ko). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). **Model Description:** - **Developed by:** Language Technology Research Group at the University of Helsinki - **Model Type:** Translation (transformer-big) - **Release**: 2022-07-28 - **License:** CC-BY-4.0 - **Language(s):** - Source Language(s): - Target Language(s): - Valid Target Language Labels: - **Original Model**: [opusTCv20210807-sepvoc_transformer-big_2022-07-28.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-kor/opusTCv20210807-sepvoc_transformer-big_2022-07-28.zip) - **Resources for more information:** - [OPUS-MT-train GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train) - More information about released models for this language pair: [OPUS-MT eng-kor README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-kor/README.md) - [More information about MarianNMT models in the transformers library](https://huggingface.co/docs/transformers/model_doc/marian) - [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/ This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id<<` (id = valid target language ID), e.g. `>><<` ## Uses This model can be used for translation and text-to-text generation. ## Risks, Limitations and Biases **CONTENT WARNING: Readers should be aware that the model is trained on various public data sets that may contain content that is disturbing, offensive, and can propagate historical and current stereotypes.** Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). ## How to Get Started With the Model A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ "2, 4, 6 etc. are even numbers.", "Yes." ] model_name = "pytorch-models/opus-mt-tc-big-en-ko" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # 2, 4, 6 등은 짝수입니다. # 그래 ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-ko") print(pipe("2, 4, 6 etc. are even numbers.")) # expected output: 2, 4, 6 등은 짝수입니다. ``` ## Training - **Data**: opusTCv20210807 ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) - **Pre-processing**: SentencePiece (spm32k,spm32k) - **Model Type:** transformer-big - **Original MarianNMT Model**: [opusTCv20210807-sepvoc_transformer-big_2022-07-28.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-kor/opusTCv20210807-sepvoc_transformer-big_2022-07-28.zip) - **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train) ## Evaluation * test set translations: [opusTCv20210807-sepvoc_transformer-big_2022-07-28.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-kor/opusTCv20210807-sepvoc_transformer-big_2022-07-28.test.txt) * test set scores: [opusTCv20210807-sepvoc_transformer-big_2022-07-28.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-kor/opusTCv20210807-sepvoc_transformer-big_2022-07-28.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| ## Citation Information * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 8b9f0b0 * port time: Fri Aug 12 11:02:03 EEST 2022 * port machine: LM0-400-22516.local
Nga3110/nha97
Nga3110
2023-10-10T10:27:55Z
1
0
diffusers
[ "diffusers", "text-to-image", "region:us" ]
text-to-image
2023-10-10T09:59:36Z
--- library_name: diffusers pipeline_tag: text-to-image ---
Helsinki-NLP/opus-mt-tc-big-en-es
Helsinki-NLP
2023-10-10T10:27:47Z
5,042
12
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "en", "es", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T15:04:03Z
--- language: - en - es tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-en-es results: - task: name: Translation eng-spa type: translation args: eng-spa dataset: name: flores101-devtest type: flores_101 args: eng spa devtest metrics: - name: BLEU type: bleu value: 28.5 - task: name: Translation eng-spa type: translation args: eng-spa dataset: name: news-test2008 type: news-test2008 args: eng-spa metrics: - name: BLEU type: bleu value: 30.1 - task: name: Translation eng-spa type: translation args: eng-spa dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-spa metrics: - name: BLEU type: bleu value: 57.2 - task: name: Translation eng-spa type: translation args: eng-spa dataset: name: tico19-test type: tico19-test args: eng-spa metrics: - name: BLEU type: bleu value: 53.0 - task: name: Translation eng-spa type: translation args: eng-spa dataset: name: newstest2009 type: wmt-2009-news args: eng-spa metrics: - name: BLEU type: bleu value: 30.2 - task: name: Translation eng-spa type: translation args: eng-spa dataset: name: newstest2010 type: wmt-2010-news args: eng-spa metrics: - name: BLEU type: bleu value: 37.6 - task: name: Translation eng-spa type: translation args: eng-spa dataset: name: newstest2011 type: wmt-2011-news args: eng-spa metrics: - name: BLEU type: bleu value: 38.9 - task: name: Translation eng-spa type: translation args: eng-spa dataset: name: newstest2012 type: wmt-2012-news args: eng-spa metrics: - name: BLEU type: bleu value: 39.5 - task: name: Translation eng-spa type: translation args: eng-spa dataset: name: newstest2013 type: wmt-2013-news args: eng-spa metrics: - name: BLEU type: bleu value: 35.9 --- # opus-mt-tc-big-en-es Neural machine translation model for translating from English (en) to Spanish (es). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-03-13 * source language(s): eng * target language(s): spa * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-03-13.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-spa/opusTCv20210807+bt_transformer-big_2022-03-13.zip) * more information released models: [OPUS-MT eng-spa README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-spa/README.md) ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ "A wasp stung him and he had an allergic reaction.", "I love nature." ] model_name = "pytorch-models/opus-mt-tc-big-en-es" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # Una avispa lo picó y tuvo una reacción alérgica. # Me encanta la naturaleza. ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-es") print(pipe("A wasp stung him and he had an allergic reaction.")) # expected output: Una avispa lo picó y tuvo una reacción alérgica. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-13.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-spa/opusTCv20210807+bt_transformer-big_2022-03-13.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-spa/opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | eng-spa | tatoeba-test-v2021-08-07 | 0.73863 | 57.2 | 16583 | 134710 | | eng-spa | flores101-devtest | 0.56440 | 28.5 | 1012 | 29199 | | eng-spa | newssyscomb2009 | 0.58415 | 31.5 | 502 | 12503 | | eng-spa | news-test2008 | 0.56707 | 30.1 | 2051 | 52586 | | eng-spa | newstest2009 | 0.57836 | 30.2 | 2525 | 68111 | | eng-spa | newstest2010 | 0.62357 | 37.6 | 2489 | 65480 | | eng-spa | newstest2011 | 0.62415 | 38.9 | 3003 | 79476 | | eng-spa | newstest2012 | 0.63031 | 39.5 | 3003 | 79006 | | eng-spa | newstest2013 | 0.60354 | 35.9 | 3000 | 70528 | | eng-spa | tico19-test | 0.73554 | 53.0 | 2100 | 66563 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 18:03:53 EEST 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-en-fi
Helsinki-NLP
2023-10-10T10:26:43Z
1,100
2
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "en", "fi", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-03-22T12:45:06Z
--- language: - en - fi tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-en-fi results: - task: name: Translation eng-fin type: translation args: eng-fin dataset: name: flores101-devtest type: flores_101 args: eng fin devtest metrics: - name: BLEU type: bleu value: 27.6 - task: name: Translation eng-fin type: translation args: eng-fin dataset: name: newsdev2015 type: newsdev2015 args: eng-fin metrics: - name: BLEU type: bleu value: 24.2 - task: name: Translation eng-fin type: translation args: eng-fin dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: eng-fin metrics: - name: BLEU type: bleu value: 39.3 - task: name: Translation eng-fin type: translation args: eng-fin dataset: name: newstest2015 type: wmt-2015-news args: eng-fin metrics: - name: BLEU type: bleu value: 26.4 - task: name: Translation eng-fin type: translation args: eng-fin dataset: name: newstest2016 type: wmt-2016-news args: eng-fin metrics: - name: BLEU type: bleu value: 28.8 - task: name: Translation eng-fin type: translation args: eng-fin dataset: name: newstest2017 type: wmt-2017-news args: eng-fin metrics: - name: BLEU type: bleu value: 31.3 - task: name: Translation eng-fin type: translation args: eng-fin dataset: name: newstest2019 type: wmt-2019-news args: eng-fin metrics: - name: BLEU type: bleu value: 26.4 --- # opus-mt-tc-big-en-fi Neural machine translation model for translating from English (en) to Finnish (fi). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-03-09 * source language(s): eng * target language(s): fin * valid target language labels: >>fin<< * model: transformer (big) * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-03-09.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-fin/opusTCv20210807+bt_transformer-big_2022-03-09.zip) * more information released models: [OPUS-MT eng-fin README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-fin/README.md) * more information about the model: [MarianMT](https://huggingface.co/docs/transformers/model_doc/marian) This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id<<` (id = valid target language ID), e.g. `>>fin<<` ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ "Russia is big.", "Touch wood!" ] model_name = "pytorch-models/opus-mt-tc-big-en-fi" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # Venäjä on suuri. # Kosketa puuta! ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-fi") print(pipe("Russia is big.")) # expected output: Venäjä on suuri. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-09.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-fin/opusTCv20210807+bt_transformer-big_2022-03-09.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-09.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-fin/opusTCv20210807+bt_transformer-big_2022-03-09.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | eng-fin | tatoeba-test-v2021-08-07 | 0.64352 | 39.3 | 10690 | 65122 | | eng-fin | flores101-devtest | 0.61334 | 27.6 | 1012 | 18781 | | eng-fin | newsdev2015 | 0.58367 | 24.2 | 1500 | 23091 | | eng-fin | newstest2015 | 0.60080 | 26.4 | 1370 | 19735 | | eng-fin | newstest2016 | 0.61636 | 28.8 | 3000 | 47678 | | eng-fin | newstest2017 | 0.64381 | 31.3 | 3002 | 45269 | | eng-fin | newstest2018 | 0.55626 | 19.7 | 3000 | 44836 | | eng-fin | newstest2019 | 0.58420 | 26.4 | 1997 | 38369 | | eng-fin | newstestB2016 | 0.57554 | 23.3 | 3000 | 45766 | | eng-fin | newstestB2017 | 0.60212 | 26.8 | 3002 | 45506 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: f084bad * port time: Tue Mar 22 14:42:32 EET 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-fr-en
Helsinki-NLP
2023-10-10T10:25:45Z
1,097
2
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "en", "fr", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T16:02:39Z
--- language: - en - fr tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-fr-en results: - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: flores101-devtest type: flores_101 args: fra eng devtest metrics: - name: BLEU type: bleu value: 46.0 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: multi30k_test_2016_flickr type: multi30k-2016_flickr args: fra-eng metrics: - name: BLEU type: bleu value: 49.7 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: multi30k_test_2017_flickr type: multi30k-2017_flickr args: fra-eng metrics: - name: BLEU type: bleu value: 52.0 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: multi30k_test_2017_mscoco type: multi30k-2017_mscoco args: fra-eng metrics: - name: BLEU type: bleu value: 50.6 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: multi30k_test_2018_flickr type: multi30k-2018_flickr args: fra-eng metrics: - name: BLEU type: bleu value: 44.9 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: news-test2008 type: news-test2008 args: fra-eng metrics: - name: BLEU type: bleu value: 26.5 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: newsdiscussdev2015 type: newsdiscussdev2015 args: fra-eng metrics: - name: BLEU type: bleu value: 34.4 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: newsdiscusstest2015 type: newsdiscusstest2015 args: fra-eng metrics: - name: BLEU type: bleu value: 40.2 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: fra-eng metrics: - name: BLEU type: bleu value: 59.8 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: tico19-test type: tico19-test args: fra-eng metrics: - name: BLEU type: bleu value: 41.3 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: newstest2009 type: wmt-2009-news args: fra-eng metrics: - name: BLEU type: bleu value: 30.4 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: newstest2010 type: wmt-2010-news args: fra-eng metrics: - name: BLEU type: bleu value: 33.4 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: newstest2011 type: wmt-2011-news args: fra-eng metrics: - name: BLEU type: bleu value: 33.8 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: newstest2012 type: wmt-2012-news args: fra-eng metrics: - name: BLEU type: bleu value: 33.6 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: newstest2013 type: wmt-2013-news args: fra-eng metrics: - name: BLEU type: bleu value: 34.8 - task: name: Translation fra-eng type: translation args: fra-eng dataset: name: newstest2014 type: wmt-2014-news args: fra-eng metrics: - name: BLEU type: bleu value: 39.4 --- # opus-mt-tc-big-fr-en Neural machine translation model for translating from French (fr) to English (en). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-03-09 * source language(s): fra * target language(s): eng * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-03-09.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/fra-eng/opusTCv20210807+bt_transformer-big_2022-03-09.zip) * more information released models: [OPUS-MT fra-eng README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/fra-eng/README.md) ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ "J'ai adoré l'Angleterre.", "C'était la seule chose à faire." ] model_name = "pytorch-models/opus-mt-tc-big-fr-en" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # I loved England. # It was the only thing to do. ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-fr-en") print(pipe("J'ai adoré l'Angleterre.")) # expected output: I loved England. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-09.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/fra-eng/opusTCv20210807+bt_transformer-big_2022-03-09.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-09.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/fra-eng/opusTCv20210807+bt_transformer-big_2022-03-09.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | fra-eng | tatoeba-test-v2021-08-07 | 0.73772 | 59.8 | 12681 | 101754 | | fra-eng | flores101-devtest | 0.69350 | 46.0 | 1012 | 24721 | | fra-eng | multi30k_test_2016_flickr | 0.68005 | 49.7 | 1000 | 12955 | | fra-eng | multi30k_test_2017_flickr | 0.70596 | 52.0 | 1000 | 11374 | | fra-eng | multi30k_test_2017_mscoco | 0.69356 | 50.6 | 461 | 5231 | | fra-eng | multi30k_test_2018_flickr | 0.65751 | 44.9 | 1071 | 14689 | | fra-eng | newsdiscussdev2015 | 0.59008 | 34.4 | 1500 | 27759 | | fra-eng | newsdiscusstest2015 | 0.62603 | 40.2 | 1500 | 26982 | | fra-eng | newssyscomb2009 | 0.57488 | 31.1 | 502 | 11818 | | fra-eng | news-test2008 | 0.54316 | 26.5 | 2051 | 49380 | | fra-eng | newstest2009 | 0.56959 | 30.4 | 2525 | 65399 | | fra-eng | newstest2010 | 0.59561 | 33.4 | 2489 | 61711 | | fra-eng | newstest2011 | 0.60271 | 33.8 | 3003 | 74681 | | fra-eng | newstest2012 | 0.59507 | 33.6 | 3003 | 72812 | | fra-eng | newstest2013 | 0.59691 | 34.8 | 3000 | 64505 | | fra-eng | newstest2014 | 0.64533 | 39.4 | 3003 | 70708 | | fra-eng | tico19-test | 0.63326 | 41.3 | 2100 | 56323 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 19:02:28 EEST 2022 * port machine: LM0-400-22516.local
Helsinki-NLP/opus-mt-tc-big-he-en
Helsinki-NLP
2023-10-10T10:25:39Z
4,064
5
transformers
[ "transformers", "pytorch", "tf", "safetensors", "marian", "text2text-generation", "translation", "opus-mt-tc", "en", "he", "license:cc-by-4.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]
translation
2022-04-13T16:27:23Z
--- language: - en - he tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-he-en results: - task: name: Translation heb-eng type: translation args: heb-eng dataset: name: flores101-devtest type: flores_101 args: heb eng devtest metrics: - name: BLEU type: bleu value: 44.1 - task: name: Translation heb-eng type: translation args: heb-eng dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: heb-eng metrics: - name: BLEU type: bleu value: 53.8 --- # opus-mt-tc-big-he-en Neural machine translation model for translating from Hebrew (he) to English (en). This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) ``` @inproceedings{tiedemann-thottingal-2020-opus, title = "{OPUS}-{MT} {--} Building open translation services for the World", author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", month = nov, year = "2020", address = "Lisboa, Portugal", publisher = "European Association for Machine Translation", url = "https://aclanthology.org/2020.eamt-1.61", pages = "479--480", } @inproceedings{tiedemann-2020-tatoeba, title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", author = {Tiedemann, J{\"o}rg}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.139", pages = "1174--1182", } ``` ## Model info * Release: 2022-03-13 * source language(s): heb * target language(s): eng * model: transformer-big * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) * tokenization: SentencePiece (spm32k,spm32k) * original model: [opusTCv20210807+bt_transformer-big_2022-03-13.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/heb-eng/opusTCv20210807+bt_transformer-big_2022-03-13.zip) * more information released models: [OPUS-MT heb-eng README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/heb-eng/README.md) ## Usage A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ "היא שכחה לכתוב לו.", "אני רוצה לדעת מיד כשמשהו יקרה." ] model_name = "pytorch-models/opus-mt-tc-big-he-en" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) for t in translated: print( tokenizer.decode(t, skip_special_tokens=True) ) # expected output: # She forgot to write to him. # I want to know as soon as something happens. ``` You can also use OPUS-MT models with the transformers pipelines, for example: ```python from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-he-en") print(pipe("היא שכחה לכתוב לו.")) # expected output: She forgot to write to him. ``` ## Benchmarks * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-13.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/heb-eng/opusTCv20210807+bt_transformer-big_2022-03-13.test.txt) * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/heb-eng/opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt) * benchmark results: [benchmark_results.txt](benchmark_results.txt) * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | langpair | testset | chr-F | BLEU | #sent | #words | |----------|---------|-------|-------|-------|--------| | heb-eng | tatoeba-test-v2021-08-07 | 0.68565 | 53.8 | 10519 | 77427 | | heb-eng | flores101-devtest | 0.68116 | 44.1 | 1012 | 24721 | ## Acknowledgements The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. ## Model conversion info * transformers version: 4.16.2 * OPUS-MT git hash: 3405783 * port time: Wed Apr 13 19:27:12 EEST 2022 * port machine: LM0-400-22516.local
cys/Reinforce-v1
cys
2023-10-10T10:23:24Z
0
0
null
[ "CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T10:23:14Z
--- tags: - CartPole-v1 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Reinforce-v1 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics: - type: mean_reward value: 500.00 +/- 0.00 name: mean_reward verified: false --- # **Reinforce** Agent playing **CartPole-v1** This is a trained model of a **Reinforce** agent playing **CartPole-v1** . To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
mys/ggml_llava-v1.5-13b
mys
2023-10-10T10:20:06Z
1,078
53
null
[ "gguf", "llava", "lmm", "ggml", "llama.cpp", "endpoints_compatible", "region:us" ]
null
2023-10-10T10:04:00Z
--- tags: - llava - lmm - ggml - llama.cpp --- # ggml_llava-v1.5-13b This repo contains GGUF files to inference [llava-v1.5-13b](https://huggingface.co/liuhaotian/llava-v1.5-13b) with [llama.cpp](https://github.com/ggerganov/llama.cpp) end-to-end without any extra dependency. **Note**: The `mmproj-model-f16.gguf` file structure is experimental and may change. Always use the latest code in llama.cpp.
srjn/q-Taxi-v3
srjn
2023-10-10T10:16:01Z
0
0
null
[ "Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T10:15:59Z
--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-Taxi-v3 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 metrics: - type: mean_reward value: 7.56 +/- 2.71 name: mean_reward verified: false --- # **Q-Learning** Agent playing1 **Taxi-v3** This is a trained model of a **Q-Learning** agent playing **Taxi-v3** . ## Usage ```python model = load_from_hub(repo_id="srjn/q-Taxi-v3", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
Dhineshk/TestDocumentQuestionAnswering
Dhineshk
2023-10-10T10:15:36Z
4
0
transformers
[ "transformers", "pytorch", "layoutlmv2", "document-question-answering", "generated_from_trainer", "base_model:microsoft/layoutlmv2-base-uncased", "base_model:finetune:microsoft/layoutlmv2-base-uncased", "license:cc-by-nc-sa-4.0", "endpoints_compatible", "region:us" ]
document-question-answering
2023-09-27T07:48:00Z
--- license: cc-by-nc-sa-4.0 base_model: microsoft/layoutlmv2-base-uncased tags: - generated_from_trainer model-index: - name: layoutlmv2-base-uncased_finetuned_docvqa results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # layoutlmv2-base-uncased_finetuned_docvqa This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 5.3353 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.153 | 0.22 | 50 | 5.3909 | | 0.2793 | 0.44 | 100 | 5.0150 | | 0.2634 | 0.66 | 150 | 4.6620 | | 0.5192 | 0.88 | 200 | 4.7826 | | 0.3096 | 1.11 | 250 | 4.9532 | | 0.2638 | 1.33 | 300 | 5.2584 | | 0.4727 | 1.55 | 350 | 4.0943 | | 0.2763 | 1.77 | 400 | 4.8408 | | 1.0425 | 1.99 | 450 | 5.0344 | | 0.4477 | 2.21 | 500 | 4.9084 | | 0.3266 | 2.43 | 550 | 5.0996 | | 0.3085 | 2.65 | 600 | 4.4858 | | 0.4648 | 2.88 | 650 | 4.0630 | | 0.1845 | 3.1 | 700 | 5.3969 | | 0.1616 | 3.32 | 750 | 4.8225 | | 0.1752 | 3.54 | 800 | 5.2945 | | 0.1877 | 3.76 | 850 | 5.2358 | | 0.3172 | 3.98 | 900 | 5.2205 | | 0.1627 | 4.2 | 950 | 4.9991 | | 0.2548 | 4.42 | 1000 | 4.6917 | | 0.1566 | 4.65 | 1050 | 5.1266 | | 0.2616 | 4.87 | 1100 | 4.3241 | | 0.1199 | 5.09 | 1150 | 4.9821 | | 0.1372 | 5.31 | 1200 | 5.0838 | | 0.1198 | 5.53 | 1250 | 5.0156 | | 0.0558 | 5.75 | 1300 | 4.8638 | | 0.1331 | 5.97 | 1350 | 4.9492 | | 0.0689 | 6.19 | 1400 | 4.6926 | | 0.0912 | 6.42 | 1450 | 4.5153 | | 0.0495 | 6.64 | 1500 | 4.6969 | | 0.0853 | 6.86 | 1550 | 4.7690 | | 0.1072 | 7.08 | 1600 | 4.6783 | | 0.034 | 7.3 | 1650 | 4.7351 | | 0.2999 | 7.52 | 1700 | 4.5185 | | 0.0763 | 7.74 | 1750 | 4.5825 | | 0.0799 | 7.96 | 1800 | 4.7218 | | 0.0343 | 8.19 | 1850 | 5.1508 | | 0.0396 | 8.41 | 1900 | 5.4893 | | 0.033 | 8.63 | 1950 | 5.5167 | | 0.0295 | 8.85 | 2000 | 5.6252 | | 0.2303 | 9.07 | 2050 | 4.7031 | | 0.088 | 9.29 | 2100 | 4.7323 | | 0.0666 | 9.51 | 2150 | 4.8688 | | 0.0597 | 9.73 | 2200 | 5.6007 | | 0.0615 | 9.96 | 2250 | 5.5403 | | 0.1003 | 10.18 | 2300 | 5.3198 | | 0.0457 | 10.4 | 2350 | 5.4828 | | 0.0391 | 10.62 | 2400 | 5.5312 | | 0.0325 | 10.84 | 2450 | 5.7410 | | 0.0147 | 11.06 | 2500 | 5.8749 | | 0.1013 | 11.28 | 2550 | 5.6522 | | 0.001 | 11.5 | 2600 | 5.7776 | | 0.0002 | 11.73 | 2650 | 5.8431 | | 0.03 | 11.95 | 2700 | 5.9751 | | 0.0452 | 12.17 | 2750 | 5.6928 | | 0.0002 | 12.39 | 2800 | 5.6264 | | 0.0109 | 12.61 | 2850 | 5.2688 | | 0.0801 | 12.83 | 2900 | 5.2780 | | 0.0216 | 13.05 | 2950 | 5.3691 | | 0.0002 | 13.27 | 3000 | 5.5237 | | 0.0092 | 13.5 | 3050 | 5.3662 | | 0.0124 | 13.72 | 3100 | 5.4474 | | 0.0515 | 13.94 | 3150 | 5.3623 | | 0.0032 | 14.16 | 3200 | 5.4168 | | 0.0051 | 14.38 | 3250 | 5.2897 | | 0.0002 | 14.6 | 3300 | 5.3205 | | 0.014 | 14.82 | 3350 | 5.2114 | | 0.0004 | 15.04 | 3400 | 5.2342 | | 0.0104 | 15.27 | 3450 | 5.2562 | | 0.0107 | 15.49 | 3500 | 5.1112 | | 0.0002 | 15.71 | 3550 | 5.1515 | | 0.0002 | 15.93 | 3600 | 5.2054 | | 0.0002 | 16.15 | 3650 | 5.1968 | | 0.0003 | 16.37 | 3700 | 5.3196 | | 0.0246 | 16.59 | 3750 | 5.3111 | | 0.0054 | 16.81 | 3800 | 5.3335 | | 0.0001 | 17.04 | 3850 | 5.3488 | | 0.0243 | 17.26 | 3900 | 5.2597 | | 0.0217 | 17.48 | 3950 | 5.2834 | | 0.0002 | 17.7 | 4000 | 5.2947 | | 0.0002 | 17.92 | 4050 | 5.3131 | | 0.0001 | 18.14 | 4100 | 5.3240 | | 0.0016 | 18.36 | 4150 | 5.3129 | | 0.0133 | 18.58 | 4200 | 5.3241 | | 0.0002 | 18.81 | 4250 | 5.3382 | | 0.0159 | 19.03 | 4300 | 5.3764 | | 0.003 | 19.25 | 4350 | 5.3776 | | 0.0516 | 19.47 | 4400 | 5.3389 | | 0.016 | 19.69 | 4450 | 5.3275 | | 0.0105 | 19.91 | 4500 | 5.3353 | ### Framework versions - Transformers 4.33.2 - Pytorch 2.0.1+cpu - Datasets 2.14.5 - Tokenizers 0.13.3
amanpelago/pelago-sentence-transformer-v1
amanpelago
2023-10-10T10:13:38Z
1
0
sentence-transformers
[ "sentence-transformers", "pytorch", "bert", "feature-extraction", "sentence-similarity", "autotrain_compatible", "text-embeddings-inference", "endpoints_compatible", "region:us" ]
sentence-similarity
2023-10-10T04:28:10Z
--- pipeline_tag: sentence-similarity tags: - sentence-transformers - feature-extraction - sentence-similarity --- # amanpelago/pelago-sentence-transformer-v1 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. <!--- Describe your model here --> ## Usage (Sentence-Transformers) Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed: ``` pip install -U sentence-transformers ``` Then you can use the model like this: ```python from sentence_transformers import SentenceTransformer sentences = ["This is an example sentence", "Each sentence is converted"] model = SentenceTransformer('amanpelago/pelago-sentence-transformer-v1') embeddings = model.encode(sentences) print(embeddings) ``` ## Evaluation Results <!--- Describe how your model was evaluated --> For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=amanpelago/pelago-sentence-transformer-v1) ## Training The model was trained with the parameters: **DataLoader**: `torch.utils.data.dataloader.DataLoader` of length 3181 with parameters: ``` {'batch_size': 16, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'} ``` **Loss**: `sentence_transformers.losses.TripletLoss.TripletLoss` with parameters: ``` {'distance_metric': 'TripletDistanceMetric.EUCLIDEAN', 'triplet_margin': 5} ``` Parameters of the fit()-Method: ``` { "epochs": 1, "evaluation_steps": 0, "evaluator": "NoneType", "max_grad_norm": 1, "optimizer_class": "<class 'torch.optim.adamw.AdamW'>", "optimizer_params": { "lr": 2e-05 }, "scheduler": "WarmupLinear", "steps_per_epoch": null, "warmup_steps": 10000, "weight_decay": 0.01 } ``` ## Full Model Architecture ``` SentenceTransformer( (0): Transformer({'max_seq_length': 256, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False}) (2): Normalize() ) ``` ## Citing & Authors <!--- Describe where people can find more information -->
Utkarshquytech/sd-german-shepherd
Utkarshquytech
2023-10-10T10:03:20Z
0
0
diffusers
[ "diffusers", "safetensors", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "autotrain_compatible", "endpoints_compatible", "diffusers:StableDiffusionPipeline", "region:us" ]
text-to-image
2023-10-10T09:50:27Z
--- license: creativeml-openrail-m tags: - text-to-image - stable-diffusion --- ### sd-german-shepherd Dreambooth model trained by Utkarshquytech with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook Test the concept via A1111 Colab [fast-Colab-A1111](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb) Sample pictures of this concept: ![0](https://huggingface.co/Utkarshquytech/sd-german-shepherd/resolve/main/sample_images/German_Shepherd_(04).jpg) ![1](https://huggingface.co/Utkarshquytech/sd-german-shepherd/resolve/main/sample_images/German_Shepherd_(03).jpg) ![2](https://huggingface.co/Utkarshquytech/sd-german-shepherd/resolve/main/sample_images/German_Shepherd_(06).jpg) ![3](https://huggingface.co/Utkarshquytech/sd-german-shepherd/resolve/main/sample_images/German_Shepherd_(01).jpg) ![4](https://huggingface.co/Utkarshquytech/sd-german-shepherd/resolve/main/sample_images/German_Shepherd_(05).jpg) ![5](https://huggingface.co/Utkarshquytech/sd-german-shepherd/resolve/main/sample_images/German_Shepherd_(02).jpg)
szdodo/dqn-SpaceInvadersNoFrameskip-v4
szdodo
2023-10-10T10:03:15Z
0
0
stable-baselines3
[ "stable-baselines3", "SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T10:02:39Z
--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 type: SpaceInvadersNoFrameskip-v4 metrics: - type: mean_reward value: 615.00 +/- 229.92 name: mean_reward verified: false --- # **DQN** Agent playing **SpaceInvadersNoFrameskip-v4** This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3) and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo). The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo) RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/> SB3: https://github.com/DLR-RM/stable-baselines3<br/> SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib Install the RL Zoo (with SB3 and SB3-Contrib): ```bash pip install rl_zoo3 ``` ``` # Download model and save it into the logs/ folder python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga szdodo -f logs/ python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do: ``` python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga szdodo -f logs/ python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` ## Training (with the RL Zoo) ``` python -m rl_zoo3.train --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ # Upload the model and generate video (when possible) python -m rl_zoo3.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga szdodo ``` ## Hyperparameters ```python OrderedDict([('batch_size', 32), ('buffer_size', 100000), ('env_wrapper', ['stable_baselines3.common.atari_wrappers.AtariWrapper']), ('exploration_final_eps', 0.01), ('exploration_fraction', 0.1), ('frame_stack', 4), ('gradient_steps', 1), ('learning_rate', 0.0001), ('learning_starts', 100000), ('n_timesteps', 1000000.0), ('optimize_memory_usage', False), ('policy', 'CnnPolicy'), ('target_update_interval', 1000), ('train_freq', 4), ('normalize', False)]) ``` # Environment Arguments ```python {'render_mode': 'rgb_array'} ```
digiplay/elegantEntropy_v1.1
digiplay
2023-10-10T09:57:04Z
249
2
diffusers
[ "diffusers", "safetensors", "stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "license:other", "autotrain_compatible", "endpoints_compatible", "diffusers:StableDiffusionPipeline", "region:us" ]
text-to-image
2023-06-22T01:44:34Z
--- license: other tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers inference: true --- Model info : https://civitai.com/models/78341/elegant-entropy Original Author's DEMO images : ![](https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/4365ef14-2fe0-4275-90c9-ae4fd8dd0813/width=512/00004-2644148705.jpeg) ![](https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/8e703631-c2af-43f3-8fd3-c319b5374301/width=512/00001-369409155.jpeg) Sample image I made: ![05b61b0c-c47b-4506-93da-b4adc29e50ff.jpeg](https://cdn-uploads.huggingface.co/production/uploads/646c83c871d0c8a6e4455854/9L4ugnijNwHcobyewOsvB.jpeg)
chdoca/test-AI
chdoca
2023-10-10T09:42:19Z
0
1
null
[ "biology", "finance", "text-classification", "dataset:fka/awesome-chatgpt-prompts", "license:creativeml-openrail-m", "region:us" ]
text-classification
2023-09-07T07:26:02Z
--- license: creativeml-openrail-m datasets: - fka/awesome-chatgpt-prompts metrics: - accuracy pipeline_tag: text-classification tags: - biology - finance ---
lsquaremaster/ppo-lunarlander
lsquaremaster
2023-10-10T09:35:22Z
1
0
stable-baselines3
[ "stable-baselines3", "LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T07:40:24Z
--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: 277.74 +/- 10.55 name: mean_reward verified: false --- # **PPO** Agent playing **LunarLander-v2** This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```
GT4SD/multitask-text-and-chemistry-t5-small-standard
GT4SD
2023-10-10T09:30:23Z
180
2
transformers
[ "transformers", "pytorch", "safetensors", "t5", "text2text-generation", "en", "arxiv:2301.12586", "license:mit", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]
text2text-generation
2023-05-12T21:52:12Z
--- license: mit language: - en --- # Multitask Text and Chemistry T5 Multitask Text and Chemistry T5 : a multi-domain, multi-task language model to solve a wide range of tasks in both the chemical and natural language domains. Published by [Christofidellis et al.](https://arxiv.org/pdf/2301.12586.pdf) **Model Details**: The Multitask Text and Chemistry T5 variant trained using <em>t5-small</em> as its pretrained based and the <em>standard dataset</em>. **Developers**: Dimitrios Christofidellis*, Giorgio Giannone*, Jannis Born, Teodoro Laino and Matteo Manica from IBM Research and Ole Winther from Technical University of Denmark. **Distributors**: Model natively integrated into GT4SD. **Model date**: 2023. **Model type**: A Transformer-based language model that is trained on a multi-domain and a multi-task dataset by aggregating available datasets for the tasks of Forward reaction prediction, Retrosynthesis, Molecular captioning, Text-conditional de novo generation and Paragraph to actions. **Information about training algorithms, parameters, fairness constraints or other applied approaches, and features**: N.A. **Paper or other resource for more information**: The Multitask Text and Chemistry T5 [Christofidellis et al.](https://arxiv.org/pdf/2301.12586.pdf) **License**: MIT **Where to send questions or comments about the model**: Open an issue on [GT4SD repository](https://github.com/GT4SD/gt4sd-core). ## Citation ```bib @article{christofidellis2023unifying, title={Unifying Molecular and Textual Representations via Multi-task Language Modelling}, author={Christofidellis, Dimitrios and Giannone, Giorgio and Born, Jannis and Winther, Ole and Laino, Teodoro and Manica, Matteo}, journal={arXiv preprint arXiv:2301.12586}, year={2023} } ``` *equal contribution
madoe001/ppo-cleanrl-LunarLander-v2
madoe001
2023-10-10T09:29:22Z
0
0
null
[ "tensorboard", "LunarLander-v2", "ppo", "deep-reinforcement-learning", "reinforcement-learning", "custom-implementation", "deep-rl-course", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T09:29:17Z
--- tags: - LunarLander-v2 - ppo - deep-reinforcement-learning - reinforcement-learning - custom-implementation - deep-rl-course model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: -192.88 +/- 154.71 name: mean_reward verified: false --- # PPO Agent Playing LunarLander-v2 This is a trained model of a PPO agent playing LunarLander-v2. # Hyperparameters ```python {'exp_name': 'ppo' 'seed': 1 'torch_deterministic': True 'cuda': True 'track': False 'wandb_project_name': 'cleanRL' 'wandb_entity': None 'capture_video': False 'env_id': 'LunarLander-v2' 'total_timesteps': 50000 'learning_rate': 0.00025 'num_envs': 4 'num_steps': 128 'anneal_lr': True 'gae': True 'gamma': 0.99 'gae_lambda': 0.95 'num_minibatches': 4 'update_epochs': 4 'norm_adv': True 'clip_coef': 0.2 'clip_vloss': True 'ent_coef': 0.01 'vf_coef': 0.5 'max_grad_norm': 0.5 'target_kl': None 'repo_id': 'madoe001/ppo-cleanrl-LunarLander-v2' 'batch_size': 512 'minibatch_size': 128} ```
kwwww/test_16_2770
kwwww
2023-10-10T09:28:28Z
0
0
null
[ "pytorch", "generated_from_trainer", "dataset:bionlp2004", "license:apache-2.0", "region:us" ]
null
2023-10-10T03:56:15Z
--- license: apache-2.0 tags: - generated_from_trainer datasets: - bionlp2004 metrics: - precision - recall - f1 - accuracy model-index: - name: test_16_2770 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # test_16_2770 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the bionlp2004 dataset. It achieves the following results on the evaluation set: - Loss: 0.6607 - Precision: 0.7753 - Recall: 0.8003 - F1: 0.7876 - Accuracy: 0.9420 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.001 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:------:|:------:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 174 | 0.2580 | 0.5740 | 0.6811 | 0.6230 | 0.9116 | | No log | 2.0 | 348 | 0.2144 | 0.6861 | 0.7045 | 0.6952 | 0.9292 | | 0.3061 | 3.0 | 522 | 0.2026 | 0.6843 | 0.7598 | 0.7201 | 0.9337 | | 0.3061 | 4.0 | 696 | 0.1943 | 0.7174 | 0.7500 | 0.7333 | 0.9373 | | 0.3061 | 5.0 | 870 | 0.2267 | 0.6492 | 0.6586 | 0.6539 | 0.9215 | | 0.1644 | 6.0 | 1044 | 0.2055 | 0.7073 | 0.7518 | 0.7289 | 0.9365 | | 0.1644 | 7.0 | 1218 | 0.2213 | 0.6942 | 0.7513 | 0.7216 | 0.9331 | | 0.1644 | 8.0 | 1392 | 0.2047 | 0.7201 | 0.7745 | 0.7463 | 0.9375 | | 0.121 | 9.0 | 1566 | 0.2138 | 0.7214 | 0.7837 | 0.7513 | 0.9372 | | 0.121 | 10.0 | 1740 | 0.2279 | 0.6868 | 0.7769 | 0.7291 | 0.9330 | | 0.121 | 11.0 | 1914 | 0.2437 | 0.7201 | 0.7430 | 0.7314 | 0.9335 | | 0.0985 | 12.0 | 2088 | 0.2396 | 0.7210 | 0.7353 | 0.7281 | 0.9322 | | 0.0985 | 13.0 | 2262 | 0.2532 | 0.6977 | 0.7542 | 0.7248 | 0.9333 | | 0.0985 | 14.0 | 2436 | 0.2704 | 0.7227 | 0.7331 | 0.7279 | 0.9334 | | 0.0801 | 15.0 | 2610 | 0.2632 | 0.7147 | 0.7598 | 0.7366 | 0.9347 | | 0.0801 | 16.0 | 2784 | 0.2759 | 0.7110 | 0.7985 | 0.7522 | 0.9381 | | 0.0801 | 17.0 | 2958 | 0.2968 | 0.7333 | 0.7724 | 0.7523 | 0.9356 | | 0.0703 | 18.0 | 3132 | 0.2678 | 0.7169 | 0.7693 | 0.7422 | 0.9356 | | 0.0703 | 19.0 | 3306 | 0.2808 | 0.7071 | 0.7785 | 0.7411 | 0.9357 | | 0.0703 | 20.0 | 3480 | 0.2772 | 0.7103 | 0.7563 | 0.7326 | 0.9344 | | 0.0606 | 21.0 | 3654 | 0.3072 | 0.7381 | 0.7572 | 0.7476 | 0.9373 | | 0.0606 | 22.0 | 3828 | 0.3188 | 0.7152 | 0.7634 | 0.7385 | 0.9346 | | 0.0503 | 23.0 | 4002 | 0.3239 | 0.7008 | 0.7612 | 0.7297 | 0.9306 | | 0.0503 | 24.0 | 4176 | 0.3289 | 0.7190 | 0.7488 | 0.7336 | 0.9348 | | 0.0503 | 25.0 | 4350 | 0.3337 | 0.7305 | 0.7776 | 0.7533 | 0.9365 | | 0.046 | 26.0 | 4524 | 0.3233 | 0.7263 | 0.7709 | 0.7480 | 0.9358 | | 0.046 | 27.0 | 4698 | 0.3178 | 0.7239 | 0.7655 | 0.7442 | 0.9368 | | 0.046 | 28.0 | 4872 | 0.3252 | 0.7096 | 0.7801 | 0.7432 | 0.9367 | | 0.0426 | 29.0 | 5046 | 0.3322 | 0.7202 | 0.7819 | 0.7498 | 0.9369 | | 0.0426 | 30.0 | 5220 | 0.3316 | 0.7225 | 0.7785 | 0.7495 | 0.9380 | | 0.0426 | 31.0 | 5394 | 0.3721 | 0.7110 | 0.7542 | 0.7320 | 0.9322 | | 0.0383 | 32.0 | 5568 | 0.3529 | 0.7269 | 0.7619 | 0.7440 | 0.9366 | | 0.0383 | 33.0 | 5742 | 0.3476 | 0.7302 | 0.7526 | 0.7412 | 0.9350 | | 0.0383 | 34.0 | 5916 | 0.3328 | 0.7251 | 0.7632 | 0.7436 | 0.9360 | | 0.0389 | 35.0 | 6090 | 0.3397 | 0.7212 | 0.7583 | 0.7393 | 0.9356 | | 0.0389 | 36.0 | 6264 | 0.3500 | 0.7328 | 0.7641 | 0.7481 | 0.9354 | | 0.0389 | 37.0 | 6438 | 0.3474 | 0.7339 | 0.7387 | 0.7363 | 0.9345 | | 0.0325 | 38.0 | 6612 | 0.3530 | 0.7297 | 0.7765 | 0.7524 | 0.9364 | | 0.0325 | 39.0 | 6786 | 0.3731 | 0.7124 | 0.7963 | 0.7520 | 0.9355 | | 0.0325 | 40.0 | 6960 | 0.3618 | 0.7237 | 0.7522 | 0.7377 | 0.9339 | | 0.0291 | 41.0 | 7134 | 0.3641 | 0.7266 | 0.7618 | 0.7437 | 0.9349 | | 0.0291 | 42.0 | 7308 | 0.3776 | 0.7327 | 0.7749 | 0.7532 | 0.9361 | | 0.0291 | 43.0 | 7482 | 0.3596 | 0.7314 | 0.7592 | 0.7451 | 0.9348 | | 0.0304 | 44.0 | 7656 | 0.3564 | 0.7447 | 0.7506 | 0.7476 | 0.9364 | | 0.0304 | 45.0 | 7830 | 0.3891 | 0.7243 | 0.7754 | 0.7490 | 0.9358 | | 0.0305 | 46.0 | 8004 | 0.3380 | 0.7239 | 0.7580 | 0.7406 | 0.9358 | | 0.0305 | 47.0 | 8178 | 0.3861 | 0.7271 | 0.7652 | 0.7456 | 0.9362 | | 0.0305 | 48.0 | 8352 | 0.3934 | 0.7279 | 0.7688 | 0.7478 | 0.9350 | | 0.0301 | 49.0 | 8526 | 0.3685 | 0.7424 | 0.7785 | 0.7600 | 0.9369 | | 0.0301 | 50.0 | 8700 | 0.4242 | 0.7200 | 0.7551 | 0.7371 | 0.9331 | | 0.0301 | 51.0 | 8874 | 0.4039 | 0.7457 | 0.7547 | 0.7502 | 0.9363 | | 0.0254 | 52.0 | 9048 | 0.3900 | 0.7256 | 0.7645 | 0.7445 | 0.9348 | | 0.0254 | 53.0 | 9222 | 0.3629 | 0.7399 | 0.7832 | 0.7609 | 0.9378 | | 0.0254 | 54.0 | 9396 | 0.3840 | 0.7433 | 0.7735 | 0.7581 | 0.9378 | | 0.0261 | 55.0 | 9570 | 0.3835 | 0.7303 | 0.7637 | 0.7467 | 0.9356 | | 0.0261 | 56.0 | 9744 | 0.4042 | 0.7264 | 0.7612 | 0.7434 | 0.9343 | | 0.0261 | 57.0 | 9918 | 0.3912 | 0.7121 | 0.7978 | 0.7525 | 0.9363 | | 0.0253 | 58.0 | 10092 | 0.3733 | 0.7407 | 0.7690 | 0.7546 | 0.9377 | | 0.0253 | 59.0 | 10266 | 0.3972 | 0.7302 | 0.7889 | 0.7584 | 0.9363 | | 0.0253 | 60.0 | 10440 | 0.4311 | 0.7362 | 0.7522 | 0.7441 | 0.9348 | | 0.0257 | 61.0 | 10614 | 0.4097 | 0.7361 | 0.7817 | 0.7583 | 0.9372 | | 0.0257 | 62.0 | 10788 | 0.4141 | 0.7429 | 0.7801 | 0.7611 | 0.9373 | | 0.0257 | 63.0 | 10962 | 0.4130 | 0.7289 | 0.7731 | 0.7503 | 0.9367 | | 0.0224 | 64.0 | 11136 | 0.4004 | 0.7211 | 0.7837 | 0.7511 | 0.9361 | | 0.0224 | 65.0 | 11310 | 0.3668 | 0.7269 | 0.7663 | 0.7460 | 0.9361 | | 0.0224 | 66.0 | 11484 | 0.3736 | 0.7285 | 0.7875 | 0.7568 | 0.9368 | | 0.0238 | 67.0 | 11658 | 0.3700 | 0.7253 | 0.7787 | 0.7510 | 0.9362 | | 0.0238 | 68.0 | 11832 | 0.3940 | 0.7480 | 0.7562 | 0.7520 | 0.9360 | | 0.0233 | 69.0 | 12006 | 0.4209 | 0.7308 | 0.7884 | 0.7585 | 0.9369 | | 0.0233 | 70.0 | 12180 | 0.4140 | 0.7408 | 0.7718 | 0.7560 | 0.9371 | | 0.0233 | 71.0 | 12354 | 0.3971 | 0.7501 | 0.7488 | 0.7495 | 0.9356 | | 0.0223 | 72.0 | 12528 | 0.3904 | 0.7246 | 0.7918 | 0.7567 | 0.9387 | | 0.0223 | 73.0 | 12702 | 0.4087 | 0.7408 | 0.7828 | 0.7612 | 0.9379 | | 0.0223 | 74.0 | 12876 | 0.4145 | 0.7370 | 0.7942 | 0.7645 | 0.9379 | | 0.021 | 75.0 | 13050 | 0.4130 | 0.7197 | 0.7891 | 0.7528 | 0.9357 | | 0.021 | 76.0 | 13224 | 0.3953 | 0.7343 | 0.7852 | 0.7589 | 0.9368 | | 0.021 | 77.0 | 13398 | 0.3903 | 0.7551 | 0.7639 | 0.7595 | 0.9377 | | 0.0216 | 78.0 | 13572 | 0.4032 | 0.7371 | 0.7785 | 0.7572 | 0.9379 | | 0.0216 | 79.0 | 13746 | 0.4310 | 0.7500 | 0.7808 | 0.7651 | 0.9370 | | 0.0216 | 80.0 | 13920 | 0.3695 | 0.7297 | 0.7898 | 0.7586 | 0.9367 | | 0.021 | 81.0 | 14094 | 0.3793 | 0.7370 | 0.7807 | 0.7582 | 0.9371 | | 0.021 | 82.0 | 14268 | 0.4069 | 0.7427 | 0.7808 | 0.7613 | 0.9390 | | 0.021 | 83.0 | 14442 | 0.4300 | 0.7136 | 0.7803 | 0.7455 | 0.9346 | | 0.0198 | 84.0 | 14616 | 0.4073 | 0.7224 | 0.7704 | 0.7456 | 0.9356 | | 0.0198 | 85.0 | 14790 | 0.3862 | 0.7402 | 0.7708 | 0.7552 | 0.9371 | | 0.0198 | 86.0 | 14964 | 0.4018 | 0.7524 | 0.7832 | 0.7675 | 0.9390 | | 0.0211 | 87.0 | 15138 | 0.4052 | 0.7384 | 0.7745 | 0.7560 | 0.9382 | | 0.0211 | 88.0 | 15312 | 0.3972 | 0.7535 | 0.7850 | 0.7689 | 0.9397 | | 0.0211 | 89.0 | 15486 | 0.4420 | 0.7318 | 0.8008 | 0.7647 | 0.9387 | | 0.0197 | 90.0 | 15660 | 0.3784 | 0.7340 | 0.7731 | 0.7530 | 0.9372 | | 0.0197 | 91.0 | 15834 | 0.4347 | 0.7452 | 0.7884 | 0.7662 | 0.9394 | | 0.0183 | 92.0 | 16008 | 0.4245 | 0.7219 | 0.7733 | 0.7467 | 0.9358 | | 0.0183 | 93.0 | 16182 | 0.4110 | 0.7436 | 0.7835 | 0.7631 | 0.9383 | | 0.0183 | 94.0 | 16356 | 0.4004 | 0.7343 | 0.7933 | 0.7626 | 0.9386 | | 0.0192 | 95.0 | 16530 | 0.4558 | 0.7298 | 0.7861 | 0.7569 | 0.9353 | | 0.0192 | 96.0 | 16704 | 0.4076 | 0.7256 | 0.7677 | 0.7461 | 0.9343 | | 0.0192 | 97.0 | 16878 | 0.4199 | 0.7338 | 0.7814 | 0.7568 | 0.9366 | | 0.0215 | 98.0 | 17052 | 0.3818 | 0.7358 | 0.7508 | 0.7432 | 0.9351 | | 0.0215 | 99.0 | 17226 | 0.4060 | 0.7305 | 0.7870 | 0.7577 | 0.9378 | | 0.0215 | 100.0 | 17400 | 0.4262 | 0.7505 | 0.7585 | 0.7545 | 0.9361 | | 0.0186 | 101.0 | 17574 | 0.3862 | 0.7306 | 0.7745 | 0.7519 | 0.9362 | | 0.0186 | 102.0 | 17748 | 0.4218 | 0.7406 | 0.7518 | 0.7462 | 0.9349 | | 0.0186 | 103.0 | 17922 | 0.3802 | 0.7380 | 0.7852 | 0.7608 | 0.9380 | | 0.0207 | 104.0 | 18096 | 0.4168 | 0.7415 | 0.7736 | 0.7572 | 0.9375 | | 0.0207 | 105.0 | 18270 | 0.4417 | 0.7349 | 0.7844 | 0.7589 | 0.9371 | | 0.0207 | 106.0 | 18444 | 0.4423 | 0.7437 | 0.7821 | 0.7624 | 0.9375 | | 0.0177 | 107.0 | 18618 | 0.4082 | 0.7336 | 0.7879 | 0.7597 | 0.9378 | | 0.0177 | 108.0 | 18792 | 0.4681 | 0.7301 | 0.7598 | 0.7446 | 0.9339 | | 0.0177 | 109.0 | 18966 | 0.4166 | 0.7415 | 0.7929 | 0.7663 | 0.9385 | | 0.0165 | 110.0 | 19140 | 0.4409 | 0.7415 | 0.7808 | 0.7606 | 0.9369 | | 0.0165 | 111.0 | 19314 | 0.4266 | 0.7468 | 0.7798 | 0.7629 | 0.9377 | | 0.0165 | 112.0 | 19488 | 0.4671 | 0.7211 | 0.7837 | 0.7511 | 0.9343 | | 0.0161 | 113.0 | 19662 | 0.4201 | 0.7484 | 0.7796 | 0.7637 | 0.9381 | | 0.0161 | 114.0 | 19836 | 0.4184 | 0.7349 | 0.7699 | 0.7520 | 0.9363 | | 0.0174 | 115.0 | 20010 | 0.4239 | 0.7287 | 0.7871 | 0.7568 | 0.9372 | | 0.0174 | 116.0 | 20184 | 0.4236 | 0.7327 | 0.7927 | 0.7615 | 0.9370 | | 0.0174 | 117.0 | 20358 | 0.4087 | 0.7529 | 0.7801 | 0.7663 | 0.9395 | | 0.0155 | 118.0 | 20532 | 0.4413 | 0.7410 | 0.7751 | 0.7577 | 0.9359 | | 0.0155 | 119.0 | 20706 | 0.4119 | 0.7247 | 0.8008 | 0.7609 | 0.9360 | | 0.0155 | 120.0 | 20880 | 0.4476 | 0.7366 | 0.7726 | 0.7542 | 0.9370 | | 0.0145 | 121.0 | 21054 | 0.4388 | 0.7429 | 0.7585 | 0.7506 | 0.9354 | | 0.0145 | 122.0 | 21228 | 0.4221 | 0.7335 | 0.7875 | 0.7595 | 0.9365 | | 0.0145 | 123.0 | 21402 | 0.4326 | 0.7454 | 0.7898 | 0.7670 | 0.9387 | | 0.0162 | 124.0 | 21576 | 0.4151 | 0.7513 | 0.7724 | 0.7617 | 0.9377 | | 0.0162 | 125.0 | 21750 | 0.4281 | 0.7330 | 0.7871 | 0.7591 | 0.9377 | | 0.0162 | 126.0 | 21924 | 0.4078 | 0.7336 | 0.7742 | 0.7534 | 0.9362 | | 0.0177 | 127.0 | 22098 | 0.4318 | 0.7340 | 0.7877 | 0.7599 | 0.9375 | | 0.0177 | 128.0 | 22272 | 0.4145 | 0.7358 | 0.7684 | 0.7518 | 0.9358 | | 0.0177 | 129.0 | 22446 | 0.4223 | 0.7482 | 0.7661 | 0.7570 | 0.9369 | | 0.0172 | 130.0 | 22620 | 0.4315 | 0.7409 | 0.7695 | 0.7549 | 0.9361 | | 0.0172 | 131.0 | 22794 | 0.4391 | 0.7533 | 0.7621 | 0.7577 | 0.9378 | | 0.0172 | 132.0 | 22968 | 0.4387 | 0.7380 | 0.7938 | 0.7649 | 0.9380 | | 0.016 | 133.0 | 23142 | 0.4193 | 0.7380 | 0.7904 | 0.7633 | 0.9374 | | 0.016 | 134.0 | 23316 | 0.4047 | 0.7470 | 0.7614 | 0.7541 | 0.9359 | | 0.016 | 135.0 | 23490 | 0.4181 | 0.7386 | 0.7835 | 0.7604 | 0.9362 | | 0.0161 | 136.0 | 23664 | 0.4271 | 0.7404 | 0.7771 | 0.7583 | 0.9364 | | 0.0161 | 137.0 | 23838 | 0.4196 | 0.7331 | 0.7686 | 0.7504 | 0.9351 | | 0.0154 | 138.0 | 24012 | 0.4402 | 0.7405 | 0.7873 | 0.7632 | 0.9373 | | 0.0154 | 139.0 | 24186 | 0.4462 | 0.7452 | 0.7767 | 0.7606 | 0.9371 | | 0.0154 | 140.0 | 24360 | 0.4812 | 0.7377 | 0.7556 | 0.7466 | 0.9342 | | 0.0135 | 141.0 | 24534 | 0.4427 | 0.7514 | 0.7637 | 0.7575 | 0.9363 | | 0.0135 | 142.0 | 24708 | 0.4757 | 0.7391 | 0.7726 | 0.7555 | 0.9364 | | 0.0135 | 143.0 | 24882 | 0.4717 | 0.7450 | 0.7801 | 0.7621 | 0.9365 | | 0.0146 | 144.0 | 25056 | 0.4523 | 0.7422 | 0.7807 | 0.7609 | 0.9370 | | 0.0146 | 145.0 | 25230 | 0.4064 | 0.7427 | 0.7814 | 0.7616 | 0.9369 | | 0.0146 | 146.0 | 25404 | 0.4439 | 0.7458 | 0.7729 | 0.7591 | 0.9360 | | 0.015 | 147.0 | 25578 | 0.4195 | 0.7435 | 0.7861 | 0.7642 | 0.9386 | | 0.015 | 148.0 | 25752 | 0.4415 | 0.7197 | 0.7639 | 0.7412 | 0.9324 | | 0.015 | 149.0 | 25926 | 0.4849 | 0.7352 | 0.7830 | 0.7584 | 0.9365 | | 0.0152 | 150.0 | 26100 | 0.4361 | 0.7257 | 0.7933 | 0.7580 | 0.9376 | | 0.0152 | 151.0 | 26274 | 0.4563 | 0.7441 | 0.7826 | 0.7629 | 0.9362 | | 0.0152 | 152.0 | 26448 | 0.4426 | 0.7407 | 0.7839 | 0.7617 | 0.9383 | | 0.0133 | 153.0 | 26622 | 0.4379 | 0.7487 | 0.7661 | 0.7573 | 0.9366 | | 0.0133 | 154.0 | 26796 | 0.4207 | 0.7418 | 0.7819 | 0.7614 | 0.9372 | | 0.0133 | 155.0 | 26970 | 0.4504 | 0.7445 | 0.7835 | 0.7635 | 0.9379 | | 0.0129 | 156.0 | 27144 | 0.4425 | 0.7359 | 0.7668 | 0.7510 | 0.9350 | | 0.0129 | 157.0 | 27318 | 0.4406 | 0.7484 | 0.7848 | 0.7662 | 0.9384 | | 0.0129 | 158.0 | 27492 | 0.4338 | 0.7387 | 0.7745 | 0.7562 | 0.9375 | | 0.0148 | 159.0 | 27666 | 0.4249 | 0.7403 | 0.7801 | 0.7597 | 0.9381 | | 0.0148 | 160.0 | 27840 | 0.4369 | 0.7390 | 0.7859 | 0.7617 | 0.9375 | | 0.0155 | 161.0 | 28014 | 0.4376 | 0.7416 | 0.7798 | 0.7602 | 0.9374 | | 0.0155 | 162.0 | 28188 | 0.4598 | 0.7549 | 0.7774 | 0.7660 | 0.9387 | | 0.0155 | 163.0 | 28362 | 0.4303 | 0.7420 | 0.7700 | 0.7557 | 0.9361 | | 0.0132 | 164.0 | 28536 | 0.4221 | 0.7490 | 0.7798 | 0.7641 | 0.9383 | | 0.0132 | 165.0 | 28710 | 0.4498 | 0.7387 | 0.7758 | 0.7568 | 0.9362 | | 0.0132 | 166.0 | 28884 | 0.4304 | 0.7506 | 0.7888 | 0.7692 | 0.9386 | | 0.0143 | 167.0 | 29058 | 0.4085 | 0.7404 | 0.7652 | 0.7526 | 0.9369 | | 0.0143 | 168.0 | 29232 | 0.4363 | 0.7503 | 0.7677 | 0.7589 | 0.9370 | | 0.0143 | 169.0 | 29406 | 0.4310 | 0.7378 | 0.7627 | 0.7500 | 0.9358 | | 0.014 | 170.0 | 29580 | 0.4197 | 0.7469 | 0.7792 | 0.7627 | 0.9373 | | 0.014 | 171.0 | 29754 | 0.4564 | 0.7534 | 0.7983 | 0.7752 | 0.9393 | | 0.014 | 172.0 | 29928 | 0.4644 | 0.7487 | 0.7758 | 0.7620 | 0.9366 | | 0.0129 | 173.0 | 30102 | 0.4530 | 0.7180 | 0.7850 | 0.7500 | 0.9341 | | 0.0129 | 174.0 | 30276 | 0.3980 | 0.7447 | 0.7897 | 0.7665 | 0.9371 | | 0.0129 | 175.0 | 30450 | 0.4738 | 0.7439 | 0.8075 | 0.7744 | 0.9374 | | 0.0122 | 176.0 | 30624 | 0.4251 | 0.7400 | 0.7709 | 0.7552 | 0.9372 | | 0.0122 | 177.0 | 30798 | 0.4782 | 0.7374 | 0.7834 | 0.7597 | 0.9357 | | 0.0122 | 178.0 | 30972 | 0.4521 | 0.7515 | 0.7861 | 0.7684 | 0.9401 | | 0.0123 | 179.0 | 31146 | 0.4303 | 0.7576 | 0.7695 | 0.7635 | 0.9370 | | 0.0123 | 180.0 | 31320 | 0.4230 | 0.7389 | 0.7763 | 0.7572 | 0.9376 | | 0.0123 | 181.0 | 31494 | 0.4576 | 0.7475 | 0.7535 | 0.7505 | 0.9353 | | 0.0132 | 182.0 | 31668 | 0.4414 | 0.7397 | 0.7736 | 0.7563 | 0.9353 | | 0.0132 | 183.0 | 31842 | 0.4430 | 0.7428 | 0.7735 | 0.7578 | 0.9361 | | 0.0156 | 184.0 | 32016 | 0.4060 | 0.7486 | 0.7846 | 0.7662 | 0.9375 | | 0.0156 | 185.0 | 32190 | 0.4421 | 0.7461 | 0.7740 | 0.7598 | 0.9366 | | 0.0156 | 186.0 | 32364 | 0.4430 | 0.7455 | 0.7821 | 0.7633 | 0.9368 | | 0.0137 | 187.0 | 32538 | 0.4059 | 0.7488 | 0.7745 | 0.7614 | 0.9380 | | 0.0137 | 188.0 | 32712 | 0.4546 | 0.7648 | 0.7693 | 0.7670 | 0.9388 | | 0.0137 | 189.0 | 32886 | 0.4378 | 0.7398 | 0.7891 | 0.7637 | 0.9384 | | 0.0118 | 190.0 | 33060 | 0.4445 | 0.7561 | 0.7976 | 0.7763 | 0.9396 | | 0.0118 | 191.0 | 33234 | 0.4536 | 0.7626 | 0.7745 | 0.7685 | 0.9389 | | 0.0118 | 192.0 | 33408 | 0.4277 | 0.7469 | 0.7700 | 0.7583 | 0.9355 | | 0.0117 | 193.0 | 33582 | 0.4446 | 0.7399 | 0.7911 | 0.7647 | 0.9378 | | 0.0117 | 194.0 | 33756 | 0.4530 | 0.7556 | 0.7654 | 0.7604 | 0.9360 | | 0.0117 | 195.0 | 33930 | 0.4741 | 0.7405 | 0.7713 | 0.7556 | 0.9358 | | 0.0125 | 196.0 | 34104 | 0.4256 | 0.7408 | 0.7853 | 0.7624 | 0.9375 | | 0.0125 | 197.0 | 34278 | 0.4774 | 0.7591 | 0.7850 | 0.7718 | 0.9375 | | 0.0125 | 198.0 | 34452 | 0.4282 | 0.7428 | 0.7823 | 0.7620 | 0.9366 | | 0.0146 | 199.0 | 34626 | 0.4427 | 0.7527 | 0.7812 | 0.7667 | 0.9383 | | 0.0146 | 200.0 | 34800 | 0.4572 | 0.7424 | 0.7796 | 0.7605 | 0.9356 | | 0.0146 | 201.0 | 34974 | 0.4586 | 0.7526 | 0.7691 | 0.7608 | 0.9365 | | 0.0119 | 202.0 | 35148 | 0.4393 | 0.7412 | 0.7729 | 0.7567 | 0.9359 | | 0.0119 | 203.0 | 35322 | 0.4489 | 0.7540 | 0.7808 | 0.7672 | 0.9383 | | 0.0119 | 204.0 | 35496 | 0.4314 | 0.7498 | 0.7880 | 0.7685 | 0.9381 | | 0.0116 | 205.0 | 35670 | 0.4501 | 0.7420 | 0.7868 | 0.7637 | 0.9379 | | 0.0116 | 206.0 | 35844 | 0.4731 | 0.7589 | 0.7945 | 0.7763 | 0.9408 | | 0.0119 | 207.0 | 36018 | 0.4493 | 0.7595 | 0.7630 | 0.7612 | 0.9378 | | 0.0119 | 208.0 | 36192 | 0.4570 | 0.7508 | 0.7938 | 0.7717 | 0.9389 | | 0.0119 | 209.0 | 36366 | 0.4698 | 0.7488 | 0.7823 | 0.7652 | 0.9374 | | 0.0111 | 210.0 | 36540 | 0.4270 | 0.7456 | 0.7817 | 0.7633 | 0.9372 | | 0.0111 | 211.0 | 36714 | 0.4625 | 0.7470 | 0.7897 | 0.7677 | 0.9385 | | 0.0111 | 212.0 | 36888 | 0.4973 | 0.7254 | 0.7567 | 0.7407 | 0.9321 | | 0.0113 | 213.0 | 37062 | 0.4465 | 0.7557 | 0.7720 | 0.7638 | 0.9361 | | 0.0113 | 214.0 | 37236 | 0.4512 | 0.7569 | 0.7843 | 0.7703 | 0.9385 | | 0.0113 | 215.0 | 37410 | 0.4488 | 0.7477 | 0.7610 | 0.7543 | 0.9350 | | 0.0117 | 216.0 | 37584 | 0.4719 | 0.7524 | 0.7706 | 0.7614 | 0.9369 | | 0.0117 | 217.0 | 37758 | 0.4410 | 0.7449 | 0.7682 | 0.7564 | 0.9354 | | 0.0117 | 218.0 | 37932 | 0.4638 | 0.7537 | 0.7754 | 0.7644 | 0.9384 | | 0.0123 | 219.0 | 38106 | 0.4629 | 0.7324 | 0.7796 | 0.7552 | 0.9347 | | 0.0123 | 220.0 | 38280 | 0.4268 | 0.7688 | 0.7744 | 0.7716 | 0.9387 | | 0.0123 | 221.0 | 38454 | 0.4265 | 0.7575 | 0.7796 | 0.7684 | 0.9379 | | 0.0118 | 222.0 | 38628 | 0.4469 | 0.7496 | 0.7855 | 0.7671 | 0.9393 | | 0.0118 | 223.0 | 38802 | 0.4554 | 0.7517 | 0.7925 | 0.7716 | 0.9386 | | 0.0118 | 224.0 | 38976 | 0.4262 | 0.7447 | 0.7720 | 0.7581 | 0.9362 | | 0.0115 | 225.0 | 39150 | 0.4910 | 0.7658 | 0.7661 | 0.7659 | 0.9362 | | 0.0115 | 226.0 | 39324 | 0.5130 | 0.7545 | 0.7774 | 0.7658 | 0.9372 | | 0.0115 | 227.0 | 39498 | 0.4266 | 0.7534 | 0.7857 | 0.7692 | 0.9376 | | 0.01 | 228.0 | 39672 | 0.5057 | 0.7469 | 0.7799 | 0.7630 | 0.9385 | | 0.01 | 229.0 | 39846 | 0.4558 | 0.7404 | 0.7961 | 0.7673 | 0.9373 | | 0.0085 | 230.0 | 40020 | 0.4580 | 0.7675 | 0.7828 | 0.7751 | 0.9397 | | 0.0085 | 231.0 | 40194 | 0.5008 | 0.7576 | 0.7774 | 0.7674 | 0.9379 | | 0.0085 | 232.0 | 40368 | 0.4653 | 0.7545 | 0.7639 | 0.7592 | 0.9361 | | 0.0113 | 233.0 | 40542 | 0.4747 | 0.7344 | 0.7756 | 0.7544 | 0.9359 | | 0.0113 | 234.0 | 40716 | 0.4761 | 0.7567 | 0.7798 | 0.7681 | 0.9378 | | 0.0113 | 235.0 | 40890 | 0.4616 | 0.7532 | 0.7745 | 0.7637 | 0.9374 | | 0.0121 | 236.0 | 41064 | 0.4353 | 0.7492 | 0.7902 | 0.7691 | 0.9376 | | 0.0121 | 237.0 | 41238 | 0.5062 | 0.7379 | 0.7819 | 0.7593 | 0.9364 | | 0.0121 | 238.0 | 41412 | 0.4255 | 0.7377 | 0.7718 | 0.7544 | 0.9358 | | 0.012 | 239.0 | 41586 | 0.4816 | 0.7296 | 0.7740 | 0.7511 | 0.9350 | | 0.012 | 240.0 | 41760 | 0.4983 | 0.7507 | 0.7749 | 0.7626 | 0.9353 | | 0.012 | 241.0 | 41934 | 0.4587 | 0.7533 | 0.7857 | 0.7691 | 0.9392 | | 0.0087 | 242.0 | 42108 | 0.4976 | 0.7471 | 0.7949 | 0.7703 | 0.9391 | | 0.0087 | 243.0 | 42282 | 0.4927 | 0.7510 | 0.7717 | 0.7612 | 0.9371 | | 0.0087 | 244.0 | 42456 | 0.4677 | 0.7446 | 0.7763 | 0.7601 | 0.9362 | | 0.009 | 245.0 | 42630 | 0.4708 | 0.7528 | 0.7745 | 0.7635 | 0.9384 | | 0.009 | 246.0 | 42804 | 0.4398 | 0.7473 | 0.7632 | 0.7552 | 0.9356 | | 0.009 | 247.0 | 42978 | 0.4850 | 0.7577 | 0.7886 | 0.7729 | 0.9381 | | 0.0111 | 248.0 | 43152 | 0.4562 | 0.7456 | 0.7657 | 0.7555 | 0.9364 | | 0.0111 | 249.0 | 43326 | 0.4476 | 0.7471 | 0.7720 | 0.7594 | 0.9370 | | 0.0103 | 250.0 | 43500 | 0.4294 | 0.7628 | 0.7756 | 0.7692 | 0.9382 | | 0.0103 | 251.0 | 43674 | 0.4518 | 0.7503 | 0.7796 | 0.7646 | 0.9378 | | 0.0103 | 252.0 | 43848 | 0.4473 | 0.7552 | 0.8021 | 0.7779 | 0.9401 | | 0.0108 | 253.0 | 44022 | 0.4770 | 0.7429 | 0.7760 | 0.7591 | 0.9371 | | 0.0108 | 254.0 | 44196 | 0.4250 | 0.7636 | 0.7747 | 0.7691 | 0.9391 | | 0.0108 | 255.0 | 44370 | 0.4571 | 0.7550 | 0.7925 | 0.7733 | 0.9404 | | 0.0098 | 256.0 | 44544 | 0.4702 | 0.7534 | 0.7933 | 0.7728 | 0.9376 | | 0.0098 | 257.0 | 44718 | 0.4349 | 0.7457 | 0.8012 | 0.7725 | 0.9391 | | 0.0098 | 258.0 | 44892 | 0.4593 | 0.7603 | 0.7987 | 0.7790 | 0.9392 | | 0.0082 | 259.0 | 45066 | 0.4534 | 0.7585 | 0.7861 | 0.7720 | 0.9397 | | 0.0082 | 260.0 | 45240 | 0.4422 | 0.7447 | 0.7960 | 0.7695 | 0.9392 | | 0.0082 | 261.0 | 45414 | 0.4863 | 0.7430 | 0.8059 | 0.7732 | 0.9368 | | 0.009 | 262.0 | 45588 | 0.4416 | 0.7541 | 0.7893 | 0.7713 | 0.9379 | | 0.009 | 263.0 | 45762 | 0.4348 | 0.7636 | 0.7934 | 0.7782 | 0.9394 | | 0.009 | 264.0 | 45936 | 0.4388 | 0.7456 | 0.7979 | 0.7709 | 0.9377 | | 0.01 | 265.0 | 46110 | 0.4662 | 0.7424 | 0.7906 | 0.7657 | 0.9376 | | 0.01 | 266.0 | 46284 | 0.4444 | 0.7392 | 0.7673 | 0.7530 | 0.9364 | | 0.01 | 267.0 | 46458 | 0.4596 | 0.7477 | 0.7862 | 0.7665 | 0.9373 | | 0.0109 | 268.0 | 46632 | 0.4544 | 0.7588 | 0.7848 | 0.7716 | 0.9385 | | 0.0109 | 269.0 | 46806 | 0.5061 | 0.7548 | 0.7961 | 0.7749 | 0.9383 | | 0.0109 | 270.0 | 46980 | 0.4716 | 0.7675 | 0.7789 | 0.7731 | 0.9392 | | 0.0106 | 271.0 | 47154 | 0.4670 | 0.7523 | 0.7762 | 0.7640 | 0.9378 | | 0.0106 | 272.0 | 47328 | 0.4665 | 0.7437 | 0.7814 | 0.7621 | 0.9361 | | 0.0094 | 273.0 | 47502 | 0.4735 | 0.7483 | 0.7855 | 0.7665 | 0.9372 | | 0.0094 | 274.0 | 47676 | 0.4754 | 0.7443 | 0.7943 | 0.7685 | 0.9375 | | 0.0094 | 275.0 | 47850 | 0.4715 | 0.7527 | 0.7787 | 0.7654 | 0.9381 | | 0.0089 | 276.0 | 48024 | 0.4728 | 0.7660 | 0.7810 | 0.7734 | 0.9397 | | 0.0089 | 277.0 | 48198 | 0.4669 | 0.7573 | 0.7855 | 0.7711 | 0.9389 | | 0.0089 | 278.0 | 48372 | 0.4120 | 0.7557 | 0.7758 | 0.7656 | 0.9378 | | 0.0093 | 279.0 | 48546 | 0.4624 | 0.7426 | 0.7823 | 0.7619 | 0.9378 | | 0.0093 | 280.0 | 48720 | 0.4641 | 0.7562 | 0.7841 | 0.7699 | 0.9391 | | 0.0093 | 281.0 | 48894 | 0.4328 | 0.7500 | 0.7695 | 0.7596 | 0.9383 | | 0.0087 | 282.0 | 49068 | 0.4777 | 0.7547 | 0.7706 | 0.7625 | 0.9380 | | 0.0087 | 283.0 | 49242 | 0.4657 | 0.7526 | 0.7877 | 0.7697 | 0.9378 | | 0.0087 | 284.0 | 49416 | 0.4747 | 0.7571 | 0.7801 | 0.7684 | 0.9387 | | 0.0089 | 285.0 | 49590 | 0.4648 | 0.7487 | 0.7799 | 0.7640 | 0.9366 | | 0.0089 | 286.0 | 49764 | 0.4483 | 0.7335 | 0.7758 | 0.7541 | 0.9372 | | 0.0089 | 287.0 | 49938 | 0.4479 | 0.7642 | 0.7970 | 0.7803 | 0.9419 | | 0.0092 | 288.0 | 50112 | 0.4889 | 0.7656 | 0.7688 | 0.7672 | 0.9390 | | 0.0092 | 289.0 | 50286 | 0.4417 | 0.7663 | 0.7771 | 0.7716 | 0.9390 | | 0.0092 | 290.0 | 50460 | 0.4840 | 0.7610 | 0.7994 | 0.7797 | 0.9404 | | 0.0105 | 291.0 | 50634 | 0.4518 | 0.7604 | 0.8001 | 0.7797 | 0.9403 | | 0.0105 | 292.0 | 50808 | 0.4606 | 0.7577 | 0.7891 | 0.7731 | 0.9396 | | 0.0105 | 293.0 | 50982 | 0.4604 | 0.7654 | 0.7769 | 0.7711 | 0.9396 | | 0.0084 | 294.0 | 51156 | 0.4559 | 0.7564 | 0.7913 | 0.7735 | 0.9392 | | 0.0084 | 295.0 | 51330 | 0.4397 | 0.7561 | 0.7933 | 0.7742 | 0.9396 | | 0.008 | 296.0 | 51504 | 0.4298 | 0.7526 | 0.7909 | 0.7713 | 0.9401 | | 0.008 | 297.0 | 51678 | 0.4616 | 0.7621 | 0.7880 | 0.7749 | 0.9404 | | 0.008 | 298.0 | 51852 | 0.4714 | 0.7561 | 0.7999 | 0.7774 | 0.9409 | | 0.0088 | 299.0 | 52026 | 0.4828 | 0.7509 | 0.7763 | 0.7634 | 0.9387 | | 0.0088 | 300.0 | 52200 | 0.4897 | 0.7538 | 0.7871 | 0.7701 | 0.9388 | | 0.0088 | 301.0 | 52374 | 0.4290 | 0.7636 | 0.7810 | 0.7722 | 0.9393 | | 0.0098 | 302.0 | 52548 | 0.4747 | 0.7546 | 0.8024 | 0.7778 | 0.9411 | | 0.0098 | 303.0 | 52722 | 0.4725 | 0.7595 | 0.7724 | 0.7659 | 0.9376 | | 0.0098 | 304.0 | 52896 | 0.4325 | 0.7551 | 0.7897 | 0.7720 | 0.9390 | | 0.0076 | 305.0 | 53070 | 0.4582 | 0.7573 | 0.7772 | 0.7672 | 0.9387 | | 0.0076 | 306.0 | 53244 | 0.4364 | 0.7575 | 0.7792 | 0.7682 | 0.9387 | | 0.0076 | 307.0 | 53418 | 0.4393 | 0.7439 | 0.7925 | 0.7675 | 0.9384 | | 0.0077 | 308.0 | 53592 | 0.4559 | 0.7648 | 0.7862 | 0.7754 | 0.9394 | | 0.0077 | 309.0 | 53766 | 0.4433 | 0.7556 | 0.7943 | 0.7745 | 0.9391 | | 0.0077 | 310.0 | 53940 | 0.4418 | 0.7604 | 0.7945 | 0.7771 | 0.9402 | | 0.0094 | 311.0 | 54114 | 0.4688 | 0.7552 | 0.7841 | 0.7694 | 0.9378 | | 0.0094 | 312.0 | 54288 | 0.4746 | 0.7486 | 0.7690 | 0.7586 | 0.9351 | | 0.0094 | 313.0 | 54462 | 0.4710 | 0.7535 | 0.7981 | 0.7752 | 0.9392 | | 0.0084 | 314.0 | 54636 | 0.4606 | 0.7616 | 0.7927 | 0.7768 | 0.9386 | | 0.0084 | 315.0 | 54810 | 0.4697 | 0.7488 | 0.7817 | 0.7649 | 0.9378 | | 0.0084 | 316.0 | 54984 | 0.4446 | 0.7537 | 0.7835 | 0.7683 | 0.9380 | | 0.0084 | 317.0 | 55158 | 0.4825 | 0.7537 | 0.7868 | 0.7699 | 0.9381 | | 0.0084 | 318.0 | 55332 | 0.4835 | 0.7608 | 0.7882 | 0.7743 | 0.9390 | | 0.0066 | 319.0 | 55506 | 0.4834 | 0.7663 | 0.7830 | 0.7746 | 0.9384 | | 0.0066 | 320.0 | 55680 | 0.4519 | 0.7537 | 0.7826 | 0.7679 | 0.9381 | | 0.0066 | 321.0 | 55854 | 0.4876 | 0.7611 | 0.7906 | 0.7755 | 0.9396 | | 0.0074 | 322.0 | 56028 | 0.4718 | 0.7484 | 0.7823 | 0.7650 | 0.9384 | | 0.0074 | 323.0 | 56202 | 0.4727 | 0.7550 | 0.7753 | 0.7650 | 0.9377 | | 0.0074 | 324.0 | 56376 | 0.4820 | 0.7440 | 0.7753 | 0.7593 | 0.9375 | | 0.0078 | 325.0 | 56550 | 0.4857 | 0.7538 | 0.7765 | 0.7650 | 0.9378 | | 0.0078 | 326.0 | 56724 | 0.4881 | 0.7522 | 0.7828 | 0.7672 | 0.9384 | | 0.0078 | 327.0 | 56898 | 0.4716 | 0.7538 | 0.7884 | 0.7707 | 0.9385 | | 0.0079 | 328.0 | 57072 | 0.5031 | 0.7542 | 0.7508 | 0.7525 | 0.9335 | | 0.0079 | 329.0 | 57246 | 0.4723 | 0.7592 | 0.7916 | 0.7751 | 0.9406 | | 0.0079 | 330.0 | 57420 | 0.4659 | 0.7597 | 0.7978 | 0.7783 | 0.9400 | | 0.0071 | 331.0 | 57594 | 0.4736 | 0.7503 | 0.7918 | 0.7705 | 0.9395 | | 0.0071 | 332.0 | 57768 | 0.4928 | 0.7580 | 0.7729 | 0.7654 | 0.9373 | | 0.0071 | 333.0 | 57942 | 0.4644 | 0.7553 | 0.7920 | 0.7732 | 0.9400 | | 0.0084 | 334.0 | 58116 | 0.4374 | 0.7522 | 0.7812 | 0.7664 | 0.9382 | | 0.0084 | 335.0 | 58290 | 0.4875 | 0.7513 | 0.8057 | 0.7775 | 0.9399 | | 0.0084 | 336.0 | 58464 | 0.4719 | 0.7526 | 0.7763 | 0.7643 | 0.9374 | | 0.0082 | 337.0 | 58638 | 0.4881 | 0.7439 | 0.7900 | 0.7663 | 0.9381 | | 0.0082 | 338.0 | 58812 | 0.4615 | 0.7385 | 0.7952 | 0.7658 | 0.9388 | | 0.0082 | 339.0 | 58986 | 0.4831 | 0.7529 | 0.7659 | 0.7593 | 0.9361 | | 0.0071 | 340.0 | 59160 | 0.4570 | 0.7511 | 0.7803 | 0.7654 | 0.9372 | | 0.0071 | 341.0 | 59334 | 0.4806 | 0.7453 | 0.7934 | 0.7686 | 0.9377 | | 0.0073 | 342.0 | 59508 | 0.4975 | 0.7451 | 0.7807 | 0.7625 | 0.9373 | | 0.0073 | 343.0 | 59682 | 0.4970 | 0.7489 | 0.8010 | 0.7741 | 0.9397 | | 0.0073 | 344.0 | 59856 | 0.4881 | 0.7528 | 0.7727 | 0.7626 | 0.9380 | | 0.0068 | 345.0 | 60030 | 0.4667 | 0.7534 | 0.7879 | 0.7702 | 0.9399 | | 0.0068 | 346.0 | 60204 | 0.4656 | 0.7562 | 0.7787 | 0.7673 | 0.9383 | | 0.0068 | 347.0 | 60378 | 0.4717 | 0.7473 | 0.7907 | 0.7684 | 0.9380 | | 0.0078 | 348.0 | 60552 | 0.4204 | 0.7532 | 0.7945 | 0.7733 | 0.9398 | | 0.0078 | 349.0 | 60726 | 0.4325 | 0.7525 | 0.7835 | 0.7677 | 0.9391 | | 0.0078 | 350.0 | 60900 | 0.4657 | 0.7536 | 0.7893 | 0.7710 | 0.9384 | | 0.0078 | 351.0 | 61074 | 0.4641 | 0.7576 | 0.8026 | 0.7795 | 0.9416 | | 0.0078 | 352.0 | 61248 | 0.4661 | 0.7610 | 0.7877 | 0.7741 | 0.9395 | | 0.0078 | 353.0 | 61422 | 0.4755 | 0.7596 | 0.8019 | 0.7802 | 0.9411 | | 0.0076 | 354.0 | 61596 | 0.4923 | 0.7712 | 0.7960 | 0.7834 | 0.9413 | | 0.0076 | 355.0 | 61770 | 0.4514 | 0.7624 | 0.7857 | 0.7739 | 0.9400 | | 0.0076 | 356.0 | 61944 | 0.4318 | 0.7593 | 0.7913 | 0.7750 | 0.9402 | | 0.0071 | 357.0 | 62118 | 0.4951 | 0.7578 | 0.7940 | 0.7755 | 0.9397 | | 0.0071 | 358.0 | 62292 | 0.4920 | 0.7637 | 0.7997 | 0.7813 | 0.9406 | | 0.0071 | 359.0 | 62466 | 0.4887 | 0.7631 | 0.7844 | 0.7736 | 0.9387 | | 0.0051 | 360.0 | 62640 | 0.5305 | 0.7458 | 0.7607 | 0.7531 | 0.9343 | | 0.0051 | 361.0 | 62814 | 0.4437 | 0.7676 | 0.7697 | 0.7686 | 0.9383 | | 0.0051 | 362.0 | 62988 | 0.4742 | 0.7533 | 0.7934 | 0.7728 | 0.9399 | | 0.008 | 363.0 | 63162 | 0.4632 | 0.7551 | 0.7803 | 0.7675 | 0.9382 | | 0.008 | 364.0 | 63336 | 0.4493 | 0.7619 | 0.7861 | 0.7738 | 0.9401 | | 0.0075 | 365.0 | 63510 | 0.4681 | 0.7410 | 0.7866 | 0.7631 | 0.9375 | | 0.0075 | 366.0 | 63684 | 0.4856 | 0.7544 | 0.7799 | 0.7670 | 0.9388 | | 0.0075 | 367.0 | 63858 | 0.4339 | 0.7516 | 0.7945 | 0.7725 | 0.9389 | | 0.0065 | 368.0 | 64032 | 0.4757 | 0.7688 | 0.7837 | 0.7762 | 0.9401 | | 0.0065 | 369.0 | 64206 | 0.4946 | 0.7516 | 0.7864 | 0.7686 | 0.9383 | | 0.0065 | 370.0 | 64380 | 0.5174 | 0.7466 | 0.8006 | 0.7727 | 0.9386 | | 0.0076 | 371.0 | 64554 | 0.4378 | 0.7624 | 0.7718 | 0.7671 | 0.9379 | | 0.0076 | 372.0 | 64728 | 0.5206 | 0.7606 | 0.7828 | 0.7716 | 0.9396 | | 0.0076 | 373.0 | 64902 | 0.4914 | 0.7545 | 0.7925 | 0.7731 | 0.9390 | | 0.0053 | 374.0 | 65076 | 0.4985 | 0.7554 | 0.7949 | 0.7747 | 0.9398 | | 0.0053 | 375.0 | 65250 | 0.4903 | 0.7624 | 0.7895 | 0.7757 | 0.9402 | | 0.0053 | 376.0 | 65424 | 0.5177 | 0.7527 | 0.8001 | 0.7757 | 0.9404 | | 0.0052 | 377.0 | 65598 | 0.4793 | 0.7386 | 0.7992 | 0.7677 | 0.9385 | | 0.0052 | 378.0 | 65772 | 0.4765 | 0.7449 | 0.7713 | 0.7579 | 0.9379 | | 0.0052 | 379.0 | 65946 | 0.4642 | 0.7652 | 0.7717 | 0.7684 | 0.9386 | | 0.0075 | 380.0 | 66120 | 0.5118 | 0.7472 | 0.7873 | 0.7667 | 0.9370 | | 0.0075 | 381.0 | 66294 | 0.4688 | 0.7616 | 0.7819 | 0.7716 | 0.9392 | | 0.0075 | 382.0 | 66468 | 0.5202 | 0.7479 | 0.7859 | 0.7664 | 0.9383 | | 0.0054 | 383.0 | 66642 | 0.5144 | 0.7525 | 0.7825 | 0.7672 | 0.9386 | | 0.0054 | 384.0 | 66816 | 0.4795 | 0.7418 | 0.7873 | 0.7639 | 0.9377 | | 0.0054 | 385.0 | 66990 | 0.4762 | 0.7508 | 0.8003 | 0.7748 | 0.9392 | | 0.0059 | 386.0 | 67164 | 0.4670 | 0.7537 | 0.7947 | 0.7737 | 0.9402 | | 0.0059 | 387.0 | 67338 | 0.4721 | 0.7398 | 0.8005 | 0.7690 | 0.9381 | | 0.0069 | 388.0 | 67512 | 0.4492 | 0.7492 | 0.7961 | 0.7720 | 0.9387 | | 0.0069 | 389.0 | 67686 | 0.5070 | 0.7641 | 0.7735 | 0.7687 | 0.9394 | | 0.0069 | 390.0 | 67860 | 0.4798 | 0.7620 | 0.7803 | 0.7711 | 0.9387 | | 0.007 | 391.0 | 68034 | 0.4535 | 0.7563 | 0.7942 | 0.7748 | 0.9408 | | 0.007 | 392.0 | 68208 | 0.4686 | 0.7577 | 0.7933 | 0.7751 | 0.9400 | | 0.007 | 393.0 | 68382 | 0.4634 | 0.7589 | 0.7753 | 0.7670 | 0.9386 | | 0.0078 | 394.0 | 68556 | 0.4392 | 0.7509 | 0.8014 | 0.7753 | 0.9403 | | 0.0078 | 395.0 | 68730 | 0.4722 | 0.7420 | 0.7853 | 0.7631 | 0.9383 | | 0.0078 | 396.0 | 68904 | 0.4613 | 0.7578 | 0.7839 | 0.7706 | 0.9401 | | 0.0055 | 397.0 | 69078 | 0.5001 | 0.7575 | 0.8015 | 0.7789 | 0.9403 | | 0.0055 | 398.0 | 69252 | 0.4868 | 0.7626 | 0.7886 | 0.7754 | 0.9394 | | 0.0055 | 399.0 | 69426 | 0.4913 | 0.7507 | 0.8026 | 0.7758 | 0.9396 | | 0.0045 | 400.0 | 69600 | 0.4784 | 0.7771 | 0.7817 | 0.7794 | 0.9406 | | 0.0045 | 401.0 | 69774 | 0.4706 | 0.7757 | 0.7745 | 0.7751 | 0.9391 | | 0.0045 | 402.0 | 69948 | 0.5051 | 0.7397 | 0.7810 | 0.7598 | 0.9365 | | 0.0062 | 403.0 | 70122 | 0.5176 | 0.7586 | 0.7888 | 0.7734 | 0.9391 | | 0.0062 | 404.0 | 70296 | 0.4870 | 0.7412 | 0.7735 | 0.7570 | 0.9380 | | 0.0062 | 405.0 | 70470 | 0.5023 | 0.7441 | 0.7762 | 0.7598 | 0.9373 | | 0.0062 | 406.0 | 70644 | 0.4699 | 0.7606 | 0.7823 | 0.7713 | 0.9403 | | 0.0062 | 407.0 | 70818 | 0.5008 | 0.7518 | 0.8008 | 0.7755 | 0.9397 | | 0.0062 | 408.0 | 70992 | 0.4870 | 0.7601 | 0.7801 | 0.7700 | 0.9396 | | 0.0057 | 409.0 | 71166 | 0.4738 | 0.7552 | 0.7776 | 0.7662 | 0.9392 | | 0.0057 | 410.0 | 71340 | 0.4712 | 0.7631 | 0.7816 | 0.7722 | 0.9399 | | 0.0061 | 411.0 | 71514 | 0.4595 | 0.7635 | 0.8033 | 0.7829 | 0.9411 | | 0.0061 | 412.0 | 71688 | 0.4862 | 0.7581 | 0.7657 | 0.7619 | 0.9395 | | 0.0061 | 413.0 | 71862 | 0.4364 | 0.7621 | 0.7796 | 0.7708 | 0.9409 | | 0.005 | 414.0 | 72036 | 0.4589 | 0.7726 | 0.7857 | 0.7791 | 0.9408 | | 0.005 | 415.0 | 72210 | 0.4529 | 0.7589 | 0.7884 | 0.7734 | 0.9394 | | 0.005 | 416.0 | 72384 | 0.4667 | 0.7513 | 0.7771 | 0.7640 | 0.9388 | | 0.0053 | 417.0 | 72558 | 0.5027 | 0.7534 | 0.8023 | 0.7771 | 0.9407 | | 0.0053 | 418.0 | 72732 | 0.4874 | 0.7554 | 0.7934 | 0.7739 | 0.9400 | | 0.0053 | 419.0 | 72906 | 0.4775 | 0.7632 | 0.7934 | 0.7780 | 0.9407 | | 0.0049 | 420.0 | 73080 | 0.4605 | 0.7586 | 0.7981 | 0.7779 | 0.9418 | | 0.0049 | 421.0 | 73254 | 0.4374 | 0.7660 | 0.7900 | 0.7778 | 0.9401 | | 0.0049 | 422.0 | 73428 | 0.5087 | 0.7472 | 0.7958 | 0.7707 | 0.9385 | | 0.0056 | 423.0 | 73602 | 0.4880 | 0.7657 | 0.7974 | 0.7812 | 0.9408 | | 0.0056 | 424.0 | 73776 | 0.4488 | 0.7678 | 0.7776 | 0.7727 | 0.9396 | | 0.0056 | 425.0 | 73950 | 0.4559 | 0.7536 | 0.7902 | 0.7714 | 0.9388 | | 0.006 | 426.0 | 74124 | 0.4532 | 0.7528 | 0.8006 | 0.7760 | 0.9399 | | 0.006 | 427.0 | 74298 | 0.4693 | 0.7679 | 0.7711 | 0.7695 | 0.9380 | | 0.006 | 428.0 | 74472 | 0.4799 | 0.7580 | 0.7853 | 0.7714 | 0.9387 | | 0.0056 | 429.0 | 74646 | 0.4685 | 0.7690 | 0.7859 | 0.7773 | 0.9401 | | 0.0056 | 430.0 | 74820 | 0.4268 | 0.7468 | 0.7835 | 0.7647 | 0.9398 | | 0.0056 | 431.0 | 74994 | 0.4773 | 0.7537 | 0.7873 | 0.7701 | 0.9401 | | 0.0053 | 432.0 | 75168 | 0.5118 | 0.7501 | 0.8015 | 0.7750 | 0.9405 | | 0.0053 | 433.0 | 75342 | 0.4640 | 0.7598 | 0.7848 | 0.7721 | 0.9403 | | 0.0048 | 434.0 | 75516 | 0.4860 | 0.7640 | 0.7738 | 0.7689 | 0.9386 | | 0.0048 | 435.0 | 75690 | 0.5147 | 0.7700 | 0.8017 | 0.7855 | 0.9417 | | 0.0048 | 436.0 | 75864 | 0.4878 | 0.7557 | 0.7884 | 0.7717 | 0.9383 | | 0.0046 | 437.0 | 76038 | 0.4966 | 0.7635 | 0.8017 | 0.7822 | 0.9408 | | 0.0046 | 438.0 | 76212 | 0.4604 | 0.7448 | 0.7911 | 0.7673 | 0.9377 | | 0.0046 | 439.0 | 76386 | 0.4839 | 0.7596 | 0.7951 | 0.7769 | 0.9411 | | 0.0058 | 440.0 | 76560 | 0.4708 | 0.7476 | 0.7888 | 0.7676 | 0.9391 | | 0.0058 | 441.0 | 76734 | 0.4490 | 0.7632 | 0.7922 | 0.7774 | 0.9407 | | 0.0058 | 442.0 | 76908 | 0.4947 | 0.7613 | 0.7927 | 0.7767 | 0.9412 | | 0.0059 | 443.0 | 77082 | 0.4897 | 0.7716 | 0.7835 | 0.7775 | 0.9409 | | 0.0059 | 444.0 | 77256 | 0.5046 | 0.7500 | 0.8010 | 0.7746 | 0.9391 | | 0.0059 | 445.0 | 77430 | 0.5258 | 0.7585 | 0.7920 | 0.7749 | 0.9398 | | 0.0044 | 446.0 | 77604 | 0.4842 | 0.7675 | 0.7906 | 0.7789 | 0.9411 | | 0.0044 | 447.0 | 77778 | 0.4685 | 0.7593 | 0.7864 | 0.7726 | 0.9402 | | 0.0044 | 448.0 | 77952 | 0.4577 | 0.7629 | 0.7951 | 0.7787 | 0.9414 | | 0.0053 | 449.0 | 78126 | 0.4895 | 0.7689 | 0.7999 | 0.7841 | 0.9411 | | 0.0053 | 450.0 | 78300 | 0.5107 | 0.7650 | 0.7861 | 0.7754 | 0.9392 | | 0.0053 | 451.0 | 78474 | 0.5035 | 0.7623 | 0.7832 | 0.7726 | 0.9399 | | 0.0045 | 452.0 | 78648 | 0.5005 | 0.7485 | 0.7916 | 0.7695 | 0.9389 | | 0.0045 | 453.0 | 78822 | 0.5180 | 0.7518 | 0.7918 | 0.7713 | 0.9387 | | 0.0045 | 454.0 | 78996 | 0.5343 | 0.7341 | 0.7837 | 0.7581 | 0.9366 | | 0.0045 | 455.0 | 79170 | 0.4669 | 0.7669 | 0.7736 | 0.7702 | 0.9385 | | 0.0045 | 456.0 | 79344 | 0.5165 | 0.7749 | 0.7868 | 0.7808 | 0.9413 | | 0.0045 | 457.0 | 79518 | 0.4796 | 0.7654 | 0.7699 | 0.7676 | 0.9377 | | 0.0045 | 458.0 | 79692 | 0.4604 | 0.7682 | 0.7902 | 0.7791 | 0.9398 | | 0.0045 | 459.0 | 79866 | 0.5214 | 0.7586 | 0.8100 | 0.7835 | 0.9412 | | 0.0049 | 460.0 | 80040 | 0.4568 | 0.7582 | 0.7799 | 0.7689 | 0.9388 | | 0.0049 | 461.0 | 80214 | 0.4892 | 0.7645 | 0.7852 | 0.7747 | 0.9398 | | 0.0049 | 462.0 | 80388 | 0.4931 | 0.7583 | 0.7922 | 0.7749 | 0.9400 | | 0.0049 | 463.0 | 80562 | 0.5158 | 0.7414 | 0.8133 | 0.7757 | 0.9387 | | 0.0049 | 464.0 | 80736 | 0.5197 | 0.7661 | 0.7852 | 0.7755 | 0.9403 | | 0.0049 | 465.0 | 80910 | 0.4984 | 0.7536 | 0.7949 | 0.7737 | 0.9385 | | 0.005 | 466.0 | 81084 | 0.4820 | 0.7513 | 0.7866 | 0.7685 | 0.9383 | | 0.005 | 467.0 | 81258 | 0.4978 | 0.7672 | 0.7846 | 0.7758 | 0.9392 | | 0.005 | 468.0 | 81432 | 0.5128 | 0.7688 | 0.7832 | 0.7759 | 0.9387 | | 0.0046 | 469.0 | 81606 | 0.5195 | 0.7563 | 0.7792 | 0.7676 | 0.9383 | | 0.0046 | 470.0 | 81780 | 0.5055 | 0.7549 | 0.7931 | 0.7735 | 0.9388 | | 0.0046 | 471.0 | 81954 | 0.5097 | 0.7558 | 0.7803 | 0.7679 | 0.9387 | | 0.0049 | 472.0 | 82128 | 0.4984 | 0.7583 | 0.7864 | 0.7721 | 0.9391 | | 0.0049 | 473.0 | 82302 | 0.5183 | 0.7599 | 0.7758 | 0.7678 | 0.9382 | | 0.0049 | 474.0 | 82476 | 0.4980 | 0.7660 | 0.7988 | 0.7821 | 0.9407 | | 0.0044 | 475.0 | 82650 | 0.4859 | 0.7629 | 0.7943 | 0.7783 | 0.9392 | | 0.0044 | 476.0 | 82824 | 0.5509 | 0.7529 | 0.7803 | 0.7664 | 0.9369 | | 0.0044 | 477.0 | 82998 | 0.5148 | 0.7595 | 0.7843 | 0.7717 | 0.9388 | | 0.0042 | 478.0 | 83172 | 0.4807 | 0.7531 | 0.7904 | 0.7713 | 0.9390 | | 0.0042 | 479.0 | 83346 | 0.4915 | 0.7534 | 0.7841 | 0.7684 | 0.9390 | | 0.0054 | 480.0 | 83520 | 0.5090 | 0.7608 | 0.7576 | 0.7592 | 0.9351 | | 0.0054 | 481.0 | 83694 | 0.4662 | 0.7541 | 0.7826 | 0.7681 | 0.9382 | | 0.0054 | 482.0 | 83868 | 0.4960 | 0.7642 | 0.7735 | 0.7688 | 0.9376 | | 0.005 | 483.0 | 84042 | 0.4847 | 0.7477 | 0.8017 | 0.7738 | 0.9385 | | 0.005 | 484.0 | 84216 | 0.4850 | 0.7599 | 0.7974 | 0.7782 | 0.9400 | | 0.005 | 485.0 | 84390 | 0.5291 | 0.7610 | 0.7913 | 0.7758 | 0.9394 | | 0.0034 | 486.0 | 84564 | 0.5256 | 0.7447 | 0.8017 | 0.7722 | 0.9378 | | 0.0034 | 487.0 | 84738 | 0.4953 | 0.7704 | 0.7697 | 0.7700 | 0.9384 | | 0.0034 | 488.0 | 84912 | 0.4912 | 0.7609 | 0.7996 | 0.7798 | 0.9405 | | 0.004 | 489.0 | 85086 | 0.5076 | 0.7558 | 0.7861 | 0.7707 | 0.9379 | | 0.004 | 490.0 | 85260 | 0.4921 | 0.7336 | 0.7931 | 0.7622 | 0.9368 | | 0.004 | 491.0 | 85434 | 0.4789 | 0.7504 | 0.7812 | 0.7655 | 0.9377 | | 0.0044 | 492.0 | 85608 | 0.5116 | 0.7472 | 0.7816 | 0.7640 | 0.9383 | | 0.0044 | 493.0 | 85782 | 0.4777 | 0.7525 | 0.7844 | 0.7681 | 0.9377 | | 0.0044 | 494.0 | 85956 | 0.5414 | 0.7636 | 0.7884 | 0.7758 | 0.9392 | | 0.004 | 495.0 | 86130 | 0.5056 | 0.7565 | 0.7949 | 0.7752 | 0.9400 | | 0.004 | 496.0 | 86304 | 0.4655 | 0.7641 | 0.7844 | 0.7741 | 0.9393 | | 0.004 | 497.0 | 86478 | 0.4739 | 0.7479 | 0.7843 | 0.7656 | 0.9385 | | 0.0054 | 498.0 | 86652 | 0.4946 | 0.7629 | 0.7909 | 0.7767 | 0.9402 | | 0.0054 | 499.0 | 86826 | 0.5502 | 0.7495 | 0.8014 | 0.7746 | 0.9392 | | 0.0045 | 500.0 | 87000 | 0.4974 | 0.7721 | 0.7954 | 0.7836 | 0.9414 | | 0.0045 | 501.0 | 87174 | 0.5209 | 0.7614 | 0.7994 | 0.7799 | 0.9393 | | 0.0045 | 502.0 | 87348 | 0.5026 | 0.7644 | 0.7988 | 0.7813 | 0.9404 | | 0.0039 | 503.0 | 87522 | 0.5084 | 0.7544 | 0.7961 | 0.7747 | 0.9396 | | 0.0039 | 504.0 | 87696 | 0.5073 | 0.7638 | 0.7979 | 0.7805 | 0.9398 | | 0.0039 | 505.0 | 87870 | 0.4764 | 0.7594 | 0.7900 | 0.7744 | 0.9399 | | 0.0045 | 506.0 | 88044 | 0.5171 | 0.7596 | 0.8030 | 0.7807 | 0.9408 | | 0.0045 | 507.0 | 88218 | 0.4914 | 0.7604 | 0.7909 | 0.7754 | 0.9389 | | 0.0045 | 508.0 | 88392 | 0.4871 | 0.7607 | 0.7992 | 0.7795 | 0.9403 | | 0.0035 | 509.0 | 88566 | 0.5326 | 0.7499 | 0.8052 | 0.7766 | 0.9382 | | 0.0035 | 510.0 | 88740 | 0.5295 | 0.7626 | 0.7972 | 0.7795 | 0.9397 | | 0.0035 | 511.0 | 88914 | 0.4840 | 0.7674 | 0.7979 | 0.7824 | 0.9420 | | 0.0031 | 512.0 | 89088 | 0.5239 | 0.7603 | 0.7911 | 0.7754 | 0.9388 | | 0.0031 | 513.0 | 89262 | 0.5085 | 0.7560 | 0.7949 | 0.7749 | 0.9392 | | 0.0031 | 514.0 | 89436 | 0.4791 | 0.7512 | 0.7936 | 0.7718 | 0.9398 | | 0.0046 | 515.0 | 89610 | 0.5041 | 0.7489 | 0.7870 | 0.7675 | 0.9386 | | 0.0046 | 516.0 | 89784 | 0.4964 | 0.7587 | 0.7825 | 0.7704 | 0.9390 | | 0.0046 | 517.0 | 89958 | 0.4531 | 0.7659 | 0.7915 | 0.7785 | 0.9406 | | 0.0041 | 518.0 | 90132 | 0.5237 | 0.7605 | 0.7823 | 0.7712 | 0.9392 | | 0.0041 | 519.0 | 90306 | 0.4824 | 0.7586 | 0.7916 | 0.7748 | 0.9390 | | 0.0041 | 520.0 | 90480 | 0.4981 | 0.7499 | 0.8052 | 0.7766 | 0.9404 | | 0.0034 | 521.0 | 90654 | 0.4819 | 0.7607 | 0.7744 | 0.7674 | 0.9383 | | 0.0034 | 522.0 | 90828 | 0.4985 | 0.7687 | 0.7803 | 0.7744 | 0.9402 | | 0.0037 | 523.0 | 91002 | 0.5253 | 0.7576 | 0.7859 | 0.7715 | 0.9392 | | 0.0037 | 524.0 | 91176 | 0.4963 | 0.7606 | 0.7857 | 0.7730 | 0.9394 | | 0.0037 | 525.0 | 91350 | 0.5193 | 0.7567 | 0.7886 | 0.7723 | 0.9399 | | 0.0035 | 526.0 | 91524 | 0.4804 | 0.7638 | 0.7898 | 0.7766 | 0.9405 | | 0.0035 | 527.0 | 91698 | 0.5161 | 0.7555 | 0.7812 | 0.7681 | 0.9392 | | 0.0035 | 528.0 | 91872 | 0.5194 | 0.7498 | 0.7945 | 0.7715 | 0.9383 | | 0.0041 | 529.0 | 92046 | 0.5046 | 0.7500 | 0.7875 | 0.7683 | 0.9387 | | 0.0041 | 530.0 | 92220 | 0.4954 | 0.7517 | 0.7967 | 0.7736 | 0.9397 | | 0.0041 | 531.0 | 92394 | 0.4996 | 0.7577 | 0.7913 | 0.7741 | 0.9392 | | 0.0035 | 532.0 | 92568 | 0.5126 | 0.7661 | 0.7976 | 0.7815 | 0.9409 | | 0.0035 | 533.0 | 92742 | 0.5498 | 0.7627 | 0.7924 | 0.7772 | 0.9403 | | 0.0035 | 534.0 | 92916 | 0.5164 | 0.7485 | 0.8008 | 0.7738 | 0.9402 | | 0.0038 | 535.0 | 93090 | 0.5013 | 0.7580 | 0.7958 | 0.7764 | 0.9414 | | 0.0038 | 536.0 | 93264 | 0.4982 | 0.7552 | 0.8066 | 0.7800 | 0.9413 | | 0.0038 | 537.0 | 93438 | 0.5042 | 0.7474 | 0.7994 | 0.7725 | 0.9401 | | 0.0037 | 538.0 | 93612 | 0.5080 | 0.7701 | 0.7825 | 0.7762 | 0.9402 | | 0.0037 | 539.0 | 93786 | 0.5246 | 0.7614 | 0.7967 | 0.7787 | 0.9402 | | 0.0037 | 540.0 | 93960 | 0.4829 | 0.7586 | 0.7825 | 0.7703 | 0.9389 | | 0.0027 | 541.0 | 94134 | 0.4933 | 0.7600 | 0.7814 | 0.7706 | 0.9378 | | 0.0027 | 542.0 | 94308 | 0.5184 | 0.7519 | 0.7907 | 0.7708 | 0.9386 | | 0.0027 | 543.0 | 94482 | 0.5012 | 0.7653 | 0.8021 | 0.7833 | 0.9405 | | 0.0032 | 544.0 | 94656 | 0.5303 | 0.7568 | 0.7913 | 0.7737 | 0.9383 | | 0.0032 | 545.0 | 94830 | 0.4911 | 0.7603 | 0.7787 | 0.7694 | 0.9386 | | 0.0034 | 546.0 | 95004 | 0.5210 | 0.7597 | 0.7913 | 0.7752 | 0.9396 | | 0.0034 | 547.0 | 95178 | 0.5194 | 0.7658 | 0.7790 | 0.7724 | 0.9396 | | 0.0034 | 548.0 | 95352 | 0.5215 | 0.7549 | 0.7915 | 0.7727 | 0.9393 | | 0.004 | 549.0 | 95526 | 0.5144 | 0.7606 | 0.7853 | 0.7727 | 0.9385 | | 0.004 | 550.0 | 95700 | 0.5175 | 0.7524 | 0.7906 | 0.7710 | 0.9391 | | 0.004 | 551.0 | 95874 | 0.5131 | 0.7439 | 0.7994 | 0.7707 | 0.9369 | | 0.0031 | 552.0 | 96048 | 0.5553 | 0.7549 | 0.7826 | 0.7685 | 0.9375 | | 0.0031 | 553.0 | 96222 | 0.5453 | 0.7624 | 0.7817 | 0.7719 | 0.9387 | | 0.0031 | 554.0 | 96396 | 0.5477 | 0.7593 | 0.7949 | 0.7767 | 0.9396 | | 0.0026 | 555.0 | 96570 | 0.5526 | 0.7521 | 0.7871 | 0.7692 | 0.9391 | | 0.0026 | 556.0 | 96744 | 0.5737 | 0.7492 | 0.7780 | 0.7633 | 0.9378 | | 0.0026 | 557.0 | 96918 | 0.5081 | 0.7701 | 0.7771 | 0.7736 | 0.9384 | | 0.0028 | 558.0 | 97092 | 0.5219 | 0.7686 | 0.7834 | 0.7759 | 0.9389 | | 0.0028 | 559.0 | 97266 | 0.5459 | 0.7731 | 0.7864 | 0.7797 | 0.9398 | | 0.0028 | 560.0 | 97440 | 0.5346 | 0.7703 | 0.7825 | 0.7763 | 0.9398 | | 0.0029 | 561.0 | 97614 | 0.5723 | 0.7462 | 0.7994 | 0.7719 | 0.9387 | | 0.0029 | 562.0 | 97788 | 0.5396 | 0.7647 | 0.7924 | 0.7783 | 0.9404 | | 0.0029 | 563.0 | 97962 | 0.5643 | 0.7574 | 0.7641 | 0.7607 | 0.9372 | | 0.0025 | 564.0 | 98136 | 0.5477 | 0.7381 | 0.7844 | 0.7605 | 0.9369 | | 0.0025 | 565.0 | 98310 | 0.5084 | 0.7539 | 0.7920 | 0.7725 | 0.9389 | | 0.0025 | 566.0 | 98484 | 0.5373 | 0.7529 | 0.7967 | 0.7742 | 0.9383 | | 0.0034 | 567.0 | 98658 | 0.5236 | 0.7463 | 0.7879 | 0.7665 | 0.9371 | | 0.0034 | 568.0 | 98832 | 0.5198 | 0.7628 | 0.7819 | 0.7723 | 0.9387 | | 0.0031 | 569.0 | 99006 | 0.5266 | 0.7546 | 0.7929 | 0.7733 | 0.9392 | | 0.0031 | 570.0 | 99180 | 0.5165 | 0.7457 | 0.7886 | 0.7666 | 0.9385 | | 0.0031 | 571.0 | 99354 | 0.5218 | 0.7698 | 0.7751 | 0.7724 | 0.9385 | | 0.0026 | 572.0 | 99528 | 0.5182 | 0.7492 | 0.7720 | 0.7604 | 0.9375 | | 0.0026 | 573.0 | 99702 | 0.5420 | 0.7680 | 0.7913 | 0.7795 | 0.9403 | | 0.0026 | 574.0 | 99876 | 0.5034 | 0.7446 | 0.7963 | 0.7696 | 0.9386 | | 0.0033 | 575.0 | 100050 | 0.5401 | 0.7447 | 0.7850 | 0.7643 | 0.9378 | | 0.0033 | 576.0 | 100224 | 0.5312 | 0.7629 | 0.7774 | 0.7701 | 0.9392 | | 0.0033 | 577.0 | 100398 | 0.5671 | 0.7669 | 0.7861 | 0.7763 | 0.9397 | | 0.003 | 578.0 | 100572 | 0.5286 | 0.7548 | 0.7987 | 0.7761 | 0.9398 | | 0.003 | 579.0 | 100746 | 0.5178 | 0.7605 | 0.7875 | 0.7738 | 0.9391 | | 0.003 | 580.0 | 100920 | 0.5226 | 0.7599 | 0.7853 | 0.7724 | 0.9390 | | 0.0032 | 581.0 | 101094 | 0.5105 | 0.7485 | 0.7825 | 0.7651 | 0.9390 | | 0.0032 | 582.0 | 101268 | 0.5186 | 0.7642 | 0.7805 | 0.7723 | 0.9386 | | 0.0032 | 583.0 | 101442 | 0.5425 | 0.7485 | 0.7931 | 0.7701 | 0.9386 | | 0.0027 | 584.0 | 101616 | 0.5209 | 0.7622 | 0.7947 | 0.7781 | 0.9402 | | 0.0027 | 585.0 | 101790 | 0.4974 | 0.7614 | 0.7846 | 0.7729 | 0.9393 | | 0.0027 | 586.0 | 101964 | 0.5281 | 0.7684 | 0.7891 | 0.7786 | 0.9400 | | 0.0034 | 587.0 | 102138 | 0.5201 | 0.7597 | 0.7954 | 0.7772 | 0.9408 | | 0.0034 | 588.0 | 102312 | 0.5103 | 0.7654 | 0.7915 | 0.7782 | 0.9406 | | 0.0034 | 589.0 | 102486 | 0.4906 | 0.7654 | 0.7913 | 0.7781 | 0.9397 | | 0.0026 | 590.0 | 102660 | 0.5055 | 0.7630 | 0.7897 | 0.7761 | 0.9405 | | 0.0026 | 591.0 | 102834 | 0.5294 | 0.7616 | 0.7650 | 0.7633 | 0.9368 | | 0.0024 | 592.0 | 103008 | 0.5285 | 0.7595 | 0.8021 | 0.7802 | 0.9413 | | 0.0024 | 593.0 | 103182 | 0.5331 | 0.7625 | 0.7690 | 0.7657 | 0.9386 | | 0.0024 | 594.0 | 103356 | 0.4922 | 0.7676 | 0.7942 | 0.7807 | 0.9419 | | 0.0041 | 595.0 | 103530 | 0.4910 | 0.7532 | 0.7846 | 0.7686 | 0.9381 | | 0.0041 | 596.0 | 103704 | 0.4904 | 0.7639 | 0.7893 | 0.7764 | 0.9393 | | 0.0041 | 597.0 | 103878 | 0.5110 | 0.7704 | 0.7898 | 0.7800 | 0.9405 | | 0.0026 | 598.0 | 104052 | 0.5124 | 0.7621 | 0.7949 | 0.7781 | 0.9393 | | 0.0026 | 599.0 | 104226 | 0.5524 | 0.7565 | 0.7943 | 0.7749 | 0.9388 | | 0.0026 | 600.0 | 104400 | 0.5630 | 0.7688 | 0.7825 | 0.7755 | 0.9390 | | 0.0026 | 601.0 | 104574 | 0.5817 | 0.7640 | 0.7790 | 0.7715 | 0.9391 | | 0.0026 | 602.0 | 104748 | 0.5518 | 0.7670 | 0.7902 | 0.7784 | 0.9395 | | 0.0026 | 603.0 | 104922 | 0.5181 | 0.7692 | 0.7798 | 0.7745 | 0.9404 | | 0.003 | 604.0 | 105096 | 0.5178 | 0.7724 | 0.7848 | 0.7786 | 0.9395 | | 0.003 | 605.0 | 105270 | 0.5312 | 0.7680 | 0.7742 | 0.7711 | 0.9390 | | 0.003 | 606.0 | 105444 | 0.5384 | 0.7624 | 0.7803 | 0.7713 | 0.9388 | | 0.0022 | 607.0 | 105618 | 0.5421 | 0.7640 | 0.7861 | 0.7749 | 0.9404 | | 0.0022 | 608.0 | 105792 | 0.5437 | 0.7590 | 0.7934 | 0.7758 | 0.9401 | | 0.0022 | 609.0 | 105966 | 0.5202 | 0.7552 | 0.7918 | 0.7731 | 0.9395 | | 0.0027 | 610.0 | 106140 | 0.5404 | 0.7673 | 0.7947 | 0.7808 | 0.9404 | | 0.0027 | 611.0 | 106314 | 0.5339 | 0.7744 | 0.7852 | 0.7798 | 0.9409 | | 0.0027 | 612.0 | 106488 | 0.5324 | 0.7667 | 0.7835 | 0.7750 | 0.9394 | | 0.0025 | 613.0 | 106662 | 0.5285 | 0.7568 | 0.7940 | 0.7749 | 0.9402 | | 0.0025 | 614.0 | 106836 | 0.5031 | 0.7677 | 0.7976 | 0.7824 | 0.9402 | | 0.0026 | 615.0 | 107010 | 0.5261 | 0.7597 | 0.7931 | 0.7760 | 0.9398 | | 0.0026 | 616.0 | 107184 | 0.5660 | 0.7525 | 0.7983 | 0.7747 | 0.9397 | | 0.0026 | 617.0 | 107358 | 0.5529 | 0.7661 | 0.7852 | 0.7755 | 0.9408 | | 0.0018 | 618.0 | 107532 | 0.5499 | 0.7663 | 0.7889 | 0.7775 | 0.9402 | | 0.0018 | 619.0 | 107706 | 0.5600 | 0.7717 | 0.7870 | 0.7792 | 0.9403 | | 0.0018 | 620.0 | 107880 | 0.5538 | 0.7697 | 0.7814 | 0.7755 | 0.9403 | | 0.0016 | 621.0 | 108054 | 0.5401 | 0.7680 | 0.7868 | 0.7773 | 0.9415 | | 0.0016 | 622.0 | 108228 | 0.4978 | 0.7596 | 0.8064 | 0.7823 | 0.9416 | | 0.0016 | 623.0 | 108402 | 0.5302 | 0.7728 | 0.7826 | 0.7777 | 0.9404 | | 0.0034 | 624.0 | 108576 | 0.5106 | 0.7714 | 0.7729 | 0.7722 | 0.9391 | | 0.0034 | 625.0 | 108750 | 0.5068 | 0.7563 | 0.7931 | 0.7743 | 0.9401 | | 0.0034 | 626.0 | 108924 | 0.5524 | 0.7599 | 0.7992 | 0.7791 | 0.9410 | | 0.0027 | 627.0 | 109098 | 0.5395 | 0.7661 | 0.7832 | 0.7745 | 0.9401 | | 0.0027 | 628.0 | 109272 | 0.5157 | 0.7499 | 0.8050 | 0.7764 | 0.9396 | | 0.0027 | 629.0 | 109446 | 0.5282 | 0.7681 | 0.7945 | 0.7811 | 0.9404 | | 0.0025 | 630.0 | 109620 | 0.5317 | 0.7477 | 0.7931 | 0.7697 | 0.9395 | | 0.0025 | 631.0 | 109794 | 0.5364 | 0.7618 | 0.7832 | 0.7723 | 0.9387 | | 0.0025 | 632.0 | 109968 | 0.4884 | 0.7661 | 0.7916 | 0.7787 | 0.9403 | | 0.0024 | 633.0 | 110142 | 0.5333 | 0.7540 | 0.7963 | 0.7746 | 0.9388 | | 0.0024 | 634.0 | 110316 | 0.5084 | 0.7585 | 0.7835 | 0.7708 | 0.9397 | | 0.0024 | 635.0 | 110490 | 0.5210 | 0.7782 | 0.7808 | 0.7795 | 0.9406 | | 0.0026 | 636.0 | 110664 | 0.5327 | 0.7569 | 0.7879 | 0.7721 | 0.9395 | | 0.0026 | 637.0 | 110838 | 0.5191 | 0.7653 | 0.7882 | 0.7766 | 0.9402 | | 0.0021 | 638.0 | 111012 | 0.5605 | 0.7525 | 0.7848 | 0.7683 | 0.9386 | | 0.0021 | 639.0 | 111186 | 0.5369 | 0.7667 | 0.7943 | 0.7803 | 0.9409 | | 0.0021 | 640.0 | 111360 | 0.5572 | 0.7683 | 0.7916 | 0.7798 | 0.9404 | | 0.0023 | 641.0 | 111534 | 0.5400 | 0.7603 | 0.7909 | 0.7753 | 0.9406 | | 0.0023 | 642.0 | 111708 | 0.5253 | 0.7723 | 0.7841 | 0.7781 | 0.9404 | | 0.0023 | 643.0 | 111882 | 0.5721 | 0.7658 | 0.7900 | 0.7777 | 0.9404 | | 0.0017 | 644.0 | 112056 | 0.5509 | 0.7583 | 0.7837 | 0.7708 | 0.9398 | | 0.0017 | 645.0 | 112230 | 0.5712 | 0.7584 | 0.7850 | 0.7714 | 0.9385 | | 0.0017 | 646.0 | 112404 | 0.5586 | 0.7622 | 0.7879 | 0.7748 | 0.9397 | | 0.0018 | 647.0 | 112578 | 0.5615 | 0.7656 | 0.7859 | 0.7756 | 0.9395 | | 0.0018 | 648.0 | 112752 | 0.5791 | 0.7651 | 0.7970 | 0.7807 | 0.9402 | | 0.0018 | 649.0 | 112926 | 0.5258 | 0.7628 | 0.7808 | 0.7717 | 0.9394 | | 0.0018 | 650.0 | 113100 | 0.5469 | 0.7630 | 0.8010 | 0.7815 | 0.9406 | | 0.0018 | 651.0 | 113274 | 0.5324 | 0.7582 | 0.7987 | 0.7779 | 0.9395 | | 0.0018 | 652.0 | 113448 | 0.4993 | 0.7556 | 0.7850 | 0.7700 | 0.9376 | | 0.0035 | 653.0 | 113622 | 0.5262 | 0.7615 | 0.7871 | 0.7741 | 0.9393 | | 0.0035 | 654.0 | 113796 | 0.5184 | 0.7594 | 0.7916 | 0.7752 | 0.9397 | | 0.0035 | 655.0 | 113970 | 0.5543 | 0.7581 | 0.7969 | 0.7770 | 0.9391 | | 0.0019 | 656.0 | 114144 | 0.4987 | 0.7671 | 0.7898 | 0.7783 | 0.9398 | | 0.0019 | 657.0 | 114318 | 0.5089 | 0.7602 | 0.7886 | 0.7742 | 0.9397 | | 0.0019 | 658.0 | 114492 | 0.5449 | 0.7652 | 0.8012 | 0.7828 | 0.9413 | | 0.0016 | 659.0 | 114666 | 0.5742 | 0.7604 | 0.8006 | 0.7800 | 0.9400 | | 0.0016 | 660.0 | 114840 | 0.5332 | 0.7670 | 0.7927 | 0.7797 | 0.9396 | | 0.0019 | 661.0 | 115014 | 0.5334 | 0.7639 | 0.7949 | 0.7791 | 0.9387 | | 0.0019 | 662.0 | 115188 | 0.5694 | 0.7636 | 0.7778 | 0.7706 | 0.9386 | | 0.0019 | 663.0 | 115362 | 0.5569 | 0.7596 | 0.8046 | 0.7815 | 0.9401 | | 0.0024 | 664.0 | 115536 | 0.5129 | 0.7621 | 0.8021 | 0.7816 | 0.9413 | | 0.0024 | 665.0 | 115710 | 0.5407 | 0.7607 | 0.7999 | 0.7798 | 0.9404 | | 0.0024 | 666.0 | 115884 | 0.5797 | 0.7662 | 0.8005 | 0.7830 | 0.9400 | | 0.0021 | 667.0 | 116058 | 0.5666 | 0.7727 | 0.7718 | 0.7723 | 0.9376 | | 0.0021 | 668.0 | 116232 | 0.5306 | 0.7624 | 0.8052 | 0.7832 | 0.9411 | | 0.0021 | 669.0 | 116406 | 0.5518 | 0.7668 | 0.8035 | 0.7847 | 0.9407 | | 0.0016 | 670.0 | 116580 | 0.5288 | 0.7614 | 0.7963 | 0.7785 | 0.9406 | | 0.0016 | 671.0 | 116754 | 0.5430 | 0.7538 | 0.8082 | 0.7800 | 0.9404 | | 0.0016 | 672.0 | 116928 | 0.5247 | 0.7606 | 0.7942 | 0.7770 | 0.9391 | | 0.0025 | 673.0 | 117102 | 0.5344 | 0.7610 | 0.8003 | 0.7801 | 0.9402 | | 0.0025 | 674.0 | 117276 | 0.5360 | 0.7660 | 0.7880 | 0.7769 | 0.9396 | | 0.0025 | 675.0 | 117450 | 0.5316 | 0.7660 | 0.7958 | 0.7806 | 0.9400 | | 0.002 | 676.0 | 117624 | 0.5465 | 0.7662 | 0.7918 | 0.7788 | 0.9402 | | 0.002 | 677.0 | 117798 | 0.5607 | 0.7578 | 0.8023 | 0.7794 | 0.9399 | | 0.002 | 678.0 | 117972 | 0.5369 | 0.7659 | 0.7837 | 0.7747 | 0.9396 | | 0.0019 | 679.0 | 118146 | 0.5474 | 0.7703 | 0.7846 | 0.7774 | 0.9403 | | 0.0019 | 680.0 | 118320 | 0.5300 | 0.7694 | 0.7889 | 0.7791 | 0.9405 | | 0.0019 | 681.0 | 118494 | 0.5401 | 0.7631 | 0.7940 | 0.7782 | 0.9400 | | 0.002 | 682.0 | 118668 | 0.5301 | 0.7684 | 0.7873 | 0.7777 | 0.9397 | | 0.002 | 683.0 | 118842 | 0.5432 | 0.7659 | 0.7958 | 0.7805 | 0.9410 | | 0.0016 | 684.0 | 119016 | 0.5291 | 0.7690 | 0.7895 | 0.7791 | 0.9391 | | 0.0016 | 685.0 | 119190 | 0.5592 | 0.7522 | 0.7979 | 0.7744 | 0.9398 | | 0.0016 | 686.0 | 119364 | 0.5702 | 0.7662 | 0.7996 | 0.7825 | 0.9422 | | 0.0015 | 687.0 | 119538 | 0.5173 | 0.7621 | 0.7915 | 0.7765 | 0.9396 | | 0.0015 | 688.0 | 119712 | 0.5428 | 0.7737 | 0.7848 | 0.7792 | 0.9397 | | 0.0015 | 689.0 | 119886 | 0.5510 | 0.7609 | 0.7893 | 0.7749 | 0.9398 | | 0.0014 | 690.0 | 120060 | 0.5749 | 0.7610 | 0.7907 | 0.7756 | 0.9395 | | 0.0014 | 691.0 | 120234 | 0.5699 | 0.7636 | 0.7889 | 0.7761 | 0.9386 | | 0.0014 | 692.0 | 120408 | 0.5464 | 0.7586 | 0.8024 | 0.7799 | 0.9397 | | 0.002 | 693.0 | 120582 | 0.5264 | 0.7512 | 0.7945 | 0.7723 | 0.9391 | | 0.002 | 694.0 | 120756 | 0.5494 | 0.7561 | 0.7765 | 0.7662 | 0.9373 | | 0.002 | 695.0 | 120930 | 0.5751 | 0.7660 | 0.7834 | 0.7746 | 0.9395 | | 0.0016 | 696.0 | 121104 | 0.5758 | 0.7704 | 0.7832 | 0.7767 | 0.9392 | | 0.0016 | 697.0 | 121278 | 0.5411 | 0.7635 | 0.7736 | 0.7685 | 0.9375 | | 0.0016 | 698.0 | 121452 | 0.5433 | 0.7712 | 0.7945 | 0.7827 | 0.9417 | | 0.0018 | 699.0 | 121626 | 0.5593 | 0.7624 | 0.7754 | 0.7689 | 0.9384 | | 0.0018 | 700.0 | 121800 | 0.5865 | 0.7569 | 0.7916 | 0.7739 | 0.9401 | | 0.0018 | 701.0 | 121974 | 0.5833 | 0.7668 | 0.7880 | 0.7773 | 0.9399 | | 0.0015 | 702.0 | 122148 | 0.6080 | 0.7651 | 0.7742 | 0.7696 | 0.9388 | | 0.0015 | 703.0 | 122322 | 0.5951 | 0.7491 | 0.7929 | 0.7704 | 0.9383 | | 0.0015 | 704.0 | 122496 | 0.5523 | 0.7627 | 0.7897 | 0.7760 | 0.9407 | | 0.0015 | 705.0 | 122670 | 0.5761 | 0.7600 | 0.7911 | 0.7753 | 0.9404 | | 0.0015 | 706.0 | 122844 | 0.5807 | 0.7558 | 0.7785 | 0.7670 | 0.9385 | | 0.001 | 707.0 | 123018 | 0.6004 | 0.7621 | 0.7888 | 0.7752 | 0.9404 | | 0.001 | 708.0 | 123192 | 0.5895 | 0.7610 | 0.7911 | 0.7757 | 0.9403 | | 0.001 | 709.0 | 123366 | 0.5402 | 0.7570 | 0.7940 | 0.7751 | 0.9393 | | 0.0019 | 710.0 | 123540 | 0.5396 | 0.7575 | 0.7875 | 0.7722 | 0.9388 | | 0.0019 | 711.0 | 123714 | 0.5586 | 0.7660 | 0.7936 | 0.7796 | 0.9402 | | 0.0019 | 712.0 | 123888 | 0.5683 | 0.7728 | 0.7866 | 0.7797 | 0.9403 | | 0.0012 | 713.0 | 124062 | 0.5357 | 0.7597 | 0.7891 | 0.7741 | 0.9395 | | 0.0012 | 714.0 | 124236 | 0.5545 | 0.7608 | 0.7978 | 0.7788 | 0.9410 | | 0.0012 | 715.0 | 124410 | 0.5560 | 0.7570 | 0.7990 | 0.7775 | 0.9409 | | 0.0018 | 716.0 | 124584 | 0.5593 | 0.7516 | 0.7918 | 0.7712 | 0.9393 | | 0.0018 | 717.0 | 124758 | 0.5748 | 0.7616 | 0.7823 | 0.7718 | 0.9390 | | 0.0018 | 718.0 | 124932 | 0.5538 | 0.7656 | 0.7942 | 0.7796 | 0.9408 | | 0.0012 | 719.0 | 125106 | 0.5552 | 0.7622 | 0.7956 | 0.7786 | 0.9401 | | 0.0012 | 720.0 | 125280 | 0.5117 | 0.7664 | 0.7875 | 0.7768 | 0.9389 | | 0.0012 | 721.0 | 125454 | 0.5464 | 0.7629 | 0.7868 | 0.7746 | 0.9387 | | 0.0016 | 722.0 | 125628 | 0.5658 | 0.7519 | 0.7904 | 0.7707 | 0.9382 | | 0.0016 | 723.0 | 125802 | 0.5788 | 0.7506 | 0.7947 | 0.7720 | 0.9380 | | 0.0016 | 724.0 | 125976 | 0.5741 | 0.7683 | 0.7888 | 0.7784 | 0.9391 | | 0.001 | 725.0 | 126150 | 0.5639 | 0.7647 | 0.7983 | 0.7811 | 0.9401 | | 0.001 | 726.0 | 126324 | 0.5446 | 0.7604 | 0.7951 | 0.7774 | 0.9403 | | 0.001 | 727.0 | 126498 | 0.5589 | 0.7609 | 0.7920 | 0.7761 | 0.9400 | | 0.0011 | 728.0 | 126672 | 0.5671 | 0.7734 | 0.7916 | 0.7824 | 0.9409 | | 0.0011 | 729.0 | 126846 | 0.5457 | 0.7742 | 0.7936 | 0.7838 | 0.9413 | | 0.0007 | 730.0 | 127020 | 0.5840 | 0.7644 | 0.7904 | 0.7772 | 0.9403 | | 0.0007 | 731.0 | 127194 | 0.6136 | 0.7714 | 0.8005 | 0.7857 | 0.9406 | | 0.0007 | 732.0 | 127368 | 0.5445 | 0.7652 | 0.7933 | 0.7790 | 0.9396 | | 0.0013 | 733.0 | 127542 | 0.5537 | 0.7685 | 0.7951 | 0.7816 | 0.9403 | | 0.0013 | 734.0 | 127716 | 0.5724 | 0.7658 | 0.7897 | 0.7776 | 0.9399 | | 0.0013 | 735.0 | 127890 | 0.5680 | 0.7571 | 0.7978 | 0.7769 | 0.9396 | | 0.0012 | 736.0 | 128064 | 0.5754 | 0.7564 | 0.7990 | 0.7771 | 0.9396 | | 0.0012 | 737.0 | 128238 | 0.5418 | 0.7625 | 0.7925 | 0.7772 | 0.9390 | | 0.0012 | 738.0 | 128412 | 0.5433 | 0.7692 | 0.7920 | 0.7804 | 0.9400 | | 0.0012 | 739.0 | 128586 | 0.5430 | 0.7694 | 0.7920 | 0.7805 | 0.9412 | | 0.0012 | 740.0 | 128760 | 0.5885 | 0.7693 | 0.7920 | 0.7805 | 0.9403 | | 0.0012 | 741.0 | 128934 | 0.5722 | 0.7655 | 0.7961 | 0.7805 | 0.9402 | | 0.001 | 742.0 | 129108 | 0.5469 | 0.7640 | 0.7951 | 0.7792 | 0.9404 | | 0.001 | 743.0 | 129282 | 0.5568 | 0.7511 | 0.7942 | 0.7721 | 0.9399 | | 0.001 | 744.0 | 129456 | 0.5844 | 0.7586 | 0.8008 | 0.7792 | 0.9402 | | 0.001 | 745.0 | 129630 | 0.5727 | 0.7551 | 0.7961 | 0.7751 | 0.9391 | | 0.001 | 746.0 | 129804 | 0.5818 | 0.7589 | 0.8023 | 0.7800 | 0.9393 | | 0.001 | 747.0 | 129978 | 0.5839 | 0.7615 | 0.7922 | 0.7765 | 0.9399 | | 0.0008 | 748.0 | 130152 | 0.5749 | 0.7638 | 0.7904 | 0.7769 | 0.9399 | | 0.0008 | 749.0 | 130326 | 0.5991 | 0.7659 | 0.7958 | 0.7805 | 0.9407 | | 0.0009 | 750.0 | 130500 | 0.6038 | 0.7618 | 0.7877 | 0.7745 | 0.9396 | | 0.0009 | 751.0 | 130674 | 0.5833 | 0.7588 | 0.7999 | 0.7788 | 0.9408 | | 0.0009 | 752.0 | 130848 | 0.5638 | 0.7626 | 0.7925 | 0.7773 | 0.9399 | | 0.0012 | 753.0 | 131022 | 0.5862 | 0.7635 | 0.7970 | 0.7799 | 0.9407 | | 0.0012 | 754.0 | 131196 | 0.5842 | 0.7626 | 0.7954 | 0.7787 | 0.9403 | | 0.0012 | 755.0 | 131370 | 0.5651 | 0.7574 | 0.7972 | 0.7768 | 0.9400 | | 0.0016 | 756.0 | 131544 | 0.5734 | 0.7593 | 0.8017 | 0.7800 | 0.9401 | | 0.0016 | 757.0 | 131718 | 0.5735 | 0.7619 | 0.7983 | 0.7797 | 0.9405 | | 0.0016 | 758.0 | 131892 | 0.5512 | 0.7720 | 0.7916 | 0.7817 | 0.9414 | | 0.0009 | 759.0 | 132066 | 0.5894 | 0.7620 | 0.7864 | 0.7740 | 0.9394 | | 0.0009 | 760.0 | 132240 | 0.5505 | 0.7645 | 0.7915 | 0.7777 | 0.9393 | | 0.0009 | 761.0 | 132414 | 0.5677 | 0.7621 | 0.7967 | 0.7790 | 0.9403 | | 0.0008 | 762.0 | 132588 | 0.5627 | 0.7697 | 0.7886 | 0.7790 | 0.9409 | | 0.0008 | 763.0 | 132762 | 0.5793 | 0.7599 | 0.7947 | 0.7769 | 0.9402 | | 0.0008 | 764.0 | 132936 | 0.5742 | 0.7676 | 0.7918 | 0.7795 | 0.9406 | | 0.0012 | 765.0 | 133110 | 0.5853 | 0.7739 | 0.7873 | 0.7806 | 0.9409 | | 0.0012 | 766.0 | 133284 | 0.5557 | 0.7584 | 0.7970 | 0.7772 | 0.9391 | | 0.0012 | 767.0 | 133458 | 0.5735 | 0.7719 | 0.7857 | 0.7788 | 0.9408 | | 0.001 | 768.0 | 133632 | 0.5893 | 0.7690 | 0.7974 | 0.7830 | 0.9416 | | 0.001 | 769.0 | 133806 | 0.5809 | 0.7743 | 0.7810 | 0.7777 | 0.9399 | | 0.001 | 770.0 | 133980 | 0.5660 | 0.7666 | 0.8001 | 0.7830 | 0.9412 | | 0.0011 | 771.0 | 134154 | 0.5704 | 0.7705 | 0.7780 | 0.7742 | 0.9403 | | 0.0011 | 772.0 | 134328 | 0.5691 | 0.7617 | 0.7916 | 0.7764 | 0.9403 | | 0.0011 | 773.0 | 134502 | 0.5652 | 0.7656 | 0.7952 | 0.7801 | 0.9409 | | 0.0011 | 774.0 | 134676 | 0.5552 | 0.7668 | 0.8015 | 0.7838 | 0.9408 | | 0.0011 | 775.0 | 134850 | 0.5624 | 0.7686 | 0.7906 | 0.7794 | 0.9404 | | 0.001 | 776.0 | 135024 | 0.5560 | 0.7652 | 0.8041 | 0.7842 | 0.9413 | | 0.001 | 777.0 | 135198 | 0.5596 | 0.7611 | 0.7844 | 0.7726 | 0.9392 | | 0.001 | 778.0 | 135372 | 0.5857 | 0.7603 | 0.7846 | 0.7722 | 0.9394 | | 0.001 | 779.0 | 135546 | 0.5912 | 0.7599 | 0.7916 | 0.7754 | 0.9399 | | 0.001 | 780.0 | 135720 | 0.5629 | 0.7547 | 0.8061 | 0.7795 | 0.9406 | | 0.001 | 781.0 | 135894 | 0.5644 | 0.7676 | 0.7960 | 0.7815 | 0.9412 | | 0.0013 | 782.0 | 136068 | 0.5994 | 0.7694 | 0.7985 | 0.7837 | 0.9410 | | 0.0013 | 783.0 | 136242 | 0.6031 | 0.7608 | 0.8055 | 0.7825 | 0.9406 | | 0.0013 | 784.0 | 136416 | 0.5842 | 0.7659 | 0.7913 | 0.7784 | 0.9396 | | 0.0007 | 785.0 | 136590 | 0.5773 | 0.7709 | 0.7727 | 0.7718 | 0.9395 | | 0.0007 | 786.0 | 136764 | 0.5928 | 0.7619 | 0.8042 | 0.7825 | 0.9406 | | 0.0007 | 787.0 | 136938 | 0.5765 | 0.7761 | 0.7819 | 0.7790 | 0.9399 | | 0.0007 | 788.0 | 137112 | 0.5978 | 0.7662 | 0.8021 | 0.7837 | 0.9415 | | 0.0007 | 789.0 | 137286 | 0.5927 | 0.7690 | 0.7884 | 0.7786 | 0.9399 | | 0.0007 | 790.0 | 137460 | 0.5910 | 0.7576 | 0.7893 | 0.7732 | 0.9387 | | 0.001 | 791.0 | 137634 | 0.5718 | 0.7716 | 0.7841 | 0.7778 | 0.9398 | | 0.001 | 792.0 | 137808 | 0.5782 | 0.7659 | 0.7940 | 0.7797 | 0.9402 | | 0.001 | 793.0 | 137982 | 0.6104 | 0.7506 | 0.7828 | 0.7664 | 0.9368 | | 0.0008 | 794.0 | 138156 | 0.5699 | 0.7683 | 0.7974 | 0.7826 | 0.9410 | | 0.0008 | 795.0 | 138330 | 0.5508 | 0.7667 | 0.7943 | 0.7803 | 0.9406 | | 0.0007 | 796.0 | 138504 | 0.5677 | 0.7618 | 0.7861 | 0.7737 | 0.9397 | | 0.0007 | 797.0 | 138678 | 0.5844 | 0.7675 | 0.7929 | 0.7800 | 0.9411 | | 0.0007 | 798.0 | 138852 | 0.5848 | 0.7712 | 0.7947 | 0.7828 | 0.9410 | | 0.0005 | 799.0 | 139026 | 0.6056 | 0.7608 | 0.8006 | 0.7802 | 0.9412 | | 0.0005 | 800.0 | 139200 | 0.5993 | 0.7686 | 0.7938 | 0.7810 | 0.9407 | | 0.0005 | 801.0 | 139374 | 0.6284 | 0.7581 | 0.7942 | 0.7757 | 0.9395 | | 0.0008 | 802.0 | 139548 | 0.6304 | 0.7682 | 0.7859 | 0.7769 | 0.9391 | | 0.0008 | 803.0 | 139722 | 0.5859 | 0.7608 | 0.7769 | 0.7688 | 0.9382 | | 0.0008 | 804.0 | 139896 | 0.5932 | 0.7626 | 0.7909 | 0.7765 | 0.9398 | | 0.0009 | 805.0 | 140070 | 0.5850 | 0.7652 | 0.8030 | 0.7837 | 0.9411 | | 0.0009 | 806.0 | 140244 | 0.5932 | 0.7647 | 0.7738 | 0.7692 | 0.9391 | | 0.0009 | 807.0 | 140418 | 0.6064 | 0.7604 | 0.7875 | 0.7737 | 0.9401 | | 0.0007 | 808.0 | 140592 | 0.5680 | 0.7721 | 0.7803 | 0.7762 | 0.9391 | | 0.0007 | 809.0 | 140766 | 0.6108 | 0.7544 | 0.7895 | 0.7716 | 0.9383 | | 0.0007 | 810.0 | 140940 | 0.6156 | 0.7654 | 0.7936 | 0.7792 | 0.9397 | | 0.0008 | 811.0 | 141114 | 0.6231 | 0.7654 | 0.7834 | 0.7743 | 0.9399 | | 0.0008 | 812.0 | 141288 | 0.6274 | 0.7640 | 0.7823 | 0.7730 | 0.9387 | | 0.0008 | 813.0 | 141462 | 0.6253 | 0.7670 | 0.7951 | 0.7808 | 0.9403 | | 0.0005 | 814.0 | 141636 | 0.6335 | 0.7603 | 0.7895 | 0.7746 | 0.9396 | | 0.0005 | 815.0 | 141810 | 0.6381 | 0.7606 | 0.7884 | 0.7743 | 0.9395 | | 0.0005 | 816.0 | 141984 | 0.6253 | 0.7606 | 0.7983 | 0.7790 | 0.9401 | | 0.0006 | 817.0 | 142158 | 0.6289 | 0.7647 | 0.7889 | 0.7766 | 0.9396 | | 0.0006 | 818.0 | 142332 | 0.5973 | 0.7653 | 0.7934 | 0.7791 | 0.9410 | | 0.0006 | 819.0 | 142506 | 0.6083 | 0.7586 | 0.7958 | 0.7768 | 0.9402 | | 0.0006 | 820.0 | 142680 | 0.5842 | 0.7709 | 0.7961 | 0.7833 | 0.9413 | | 0.0006 | 821.0 | 142854 | 0.6084 | 0.7610 | 0.7992 | 0.7796 | 0.9404 | | 0.001 | 822.0 | 143028 | 0.6156 | 0.7610 | 0.7981 | 0.7791 | 0.9412 | | 0.001 | 823.0 | 143202 | 0.6018 | 0.7592 | 0.7990 | 0.7786 | 0.9408 | | 0.001 | 824.0 | 143376 | 0.5920 | 0.7628 | 0.7974 | 0.7797 | 0.9412 | | 0.0007 | 825.0 | 143550 | 0.6093 | 0.7658 | 0.7913 | 0.7783 | 0.9400 | | 0.0007 | 826.0 | 143724 | 0.6057 | 0.7636 | 0.7938 | 0.7784 | 0.9409 | | 0.0007 | 827.0 | 143898 | 0.5992 | 0.7628 | 0.8003 | 0.7811 | 0.9411 | | 0.0006 | 828.0 | 144072 | 0.6110 | 0.7717 | 0.7879 | 0.7797 | 0.9408 | | 0.0006 | 829.0 | 144246 | 0.5798 | 0.7670 | 0.7972 | 0.7818 | 0.9411 | | 0.0006 | 830.0 | 144420 | 0.5785 | 0.7685 | 0.7992 | 0.7835 | 0.9419 | | 0.0007 | 831.0 | 144594 | 0.6012 | 0.7696 | 0.7855 | 0.7775 | 0.9404 | | 0.0007 | 832.0 | 144768 | 0.6055 | 0.7649 | 0.7929 | 0.7787 | 0.9408 | | 0.0007 | 833.0 | 144942 | 0.6022 | 0.7711 | 0.7924 | 0.7816 | 0.9413 | | 0.0003 | 834.0 | 145116 | 0.6119 | 0.7718 | 0.7862 | 0.7789 | 0.9411 | | 0.0003 | 835.0 | 145290 | 0.5827 | 0.7706 | 0.7960 | 0.7831 | 0.9421 | | 0.0003 | 836.0 | 145464 | 0.5844 | 0.7682 | 0.7789 | 0.7735 | 0.9400 | | 0.001 | 837.0 | 145638 | 0.6001 | 0.7695 | 0.7947 | 0.7819 | 0.9414 | | 0.001 | 838.0 | 145812 | 0.6120 | 0.7651 | 0.7929 | 0.7787 | 0.9408 | | 0.001 | 839.0 | 145986 | 0.6139 | 0.7631 | 0.8001 | 0.7812 | 0.9412 | | 0.0007 | 840.0 | 146160 | 0.6323 | 0.7673 | 0.7855 | 0.7763 | 0.9404 | | 0.0007 | 841.0 | 146334 | 0.6773 | 0.7647 | 0.7882 | 0.7763 | 0.9401 | | 0.0005 | 842.0 | 146508 | 0.6406 | 0.7692 | 0.7916 | 0.7803 | 0.9407 | | 0.0005 | 843.0 | 146682 | 0.6117 | 0.7626 | 0.7900 | 0.7760 | 0.9400 | | 0.0005 | 844.0 | 146856 | 0.6223 | 0.7638 | 0.7846 | 0.7741 | 0.9399 | | 0.0005 | 845.0 | 147030 | 0.6309 | 0.7693 | 0.7979 | 0.7833 | 0.9407 | | 0.0005 | 846.0 | 147204 | 0.6475 | 0.7609 | 0.7999 | 0.7799 | 0.9401 | | 0.0005 | 847.0 | 147378 | 0.6018 | 0.7672 | 0.7888 | 0.7778 | 0.9401 | | 0.0008 | 848.0 | 147552 | 0.6146 | 0.7641 | 0.7967 | 0.7800 | 0.9409 | | 0.0008 | 849.0 | 147726 | 0.6105 | 0.7647 | 0.7859 | 0.7751 | 0.9402 | | 0.0008 | 850.0 | 147900 | 0.5892 | 0.7764 | 0.7911 | 0.7837 | 0.9417 | | 0.0004 | 851.0 | 148074 | 0.5999 | 0.7736 | 0.8012 | 0.7872 | 0.9421 | | 0.0004 | 852.0 | 148248 | 0.6043 | 0.7618 | 0.8017 | 0.7813 | 0.9413 | | 0.0004 | 853.0 | 148422 | 0.6227 | 0.7597 | 0.7918 | 0.7754 | 0.9409 | | 0.0004 | 854.0 | 148596 | 0.6485 | 0.7620 | 0.7888 | 0.7752 | 0.9400 | | 0.0004 | 855.0 | 148770 | 0.6376 | 0.7638 | 0.7933 | 0.7783 | 0.9408 | | 0.0004 | 856.0 | 148944 | 0.6426 | 0.7716 | 0.7965 | 0.7839 | 0.9413 | | 0.0003 | 857.0 | 149118 | 0.6455 | 0.7723 | 0.8033 | 0.7875 | 0.9413 | | 0.0003 | 858.0 | 149292 | 0.6459 | 0.7660 | 0.8086 | 0.7867 | 0.9417 | | 0.0003 | 859.0 | 149466 | 0.6244 | 0.7628 | 0.7875 | 0.7749 | 0.9399 | | 0.0003 | 860.0 | 149640 | 0.6304 | 0.7683 | 0.7810 | 0.7746 | 0.9399 | | 0.0003 | 861.0 | 149814 | 0.6419 | 0.7692 | 0.7808 | 0.7750 | 0.9400 | | 0.0003 | 862.0 | 149988 | 0.6350 | 0.7668 | 0.7992 | 0.7826 | 0.9419 | | 0.0003 | 863.0 | 150162 | 0.6327 | 0.7769 | 0.7960 | 0.7863 | 0.9414 | | 0.0003 | 864.0 | 150336 | 0.6530 | 0.7560 | 0.7934 | 0.7743 | 0.9402 | | 0.0005 | 865.0 | 150510 | 0.6452 | 0.7549 | 0.7994 | 0.7765 | 0.9409 | | 0.0005 | 866.0 | 150684 | 0.6417 | 0.7648 | 0.7857 | 0.7751 | 0.9405 | | 0.0005 | 867.0 | 150858 | 0.6240 | 0.7566 | 0.8033 | 0.7793 | 0.9418 | | 0.0004 | 868.0 | 151032 | 0.6317 | 0.7663 | 0.7956 | 0.7807 | 0.9417 | | 0.0004 | 869.0 | 151206 | 0.6258 | 0.7652 | 0.7922 | 0.7784 | 0.9410 | | 0.0004 | 870.0 | 151380 | 0.6313 | 0.7699 | 0.7961 | 0.7828 | 0.9422 | | 0.0004 | 871.0 | 151554 | 0.6250 | 0.7710 | 0.7925 | 0.7816 | 0.9409 | | 0.0004 | 872.0 | 151728 | 0.6365 | 0.7677 | 0.7902 | 0.7788 | 0.9408 | | 0.0004 | 873.0 | 151902 | 0.6250 | 0.7713 | 0.7848 | 0.7780 | 0.9408 | | 0.0004 | 874.0 | 152076 | 0.6261 | 0.7594 | 0.7965 | 0.7775 | 0.9410 | | 0.0004 | 875.0 | 152250 | 0.6320 | 0.7700 | 0.7940 | 0.7818 | 0.9414 | | 0.0004 | 876.0 | 152424 | 0.6377 | 0.7692 | 0.7969 | 0.7828 | 0.9420 | | 0.0002 | 877.0 | 152598 | 0.6272 | 0.7673 | 0.8041 | 0.7853 | 0.9420 | | 0.0002 | 878.0 | 152772 | 0.6190 | 0.7664 | 0.7994 | 0.7825 | 0.9412 | | 0.0002 | 879.0 | 152946 | 0.6321 | 0.7687 | 0.7920 | 0.7802 | 0.9407 | | 0.0003 | 880.0 | 153120 | 0.6322 | 0.7672 | 0.7933 | 0.7800 | 0.9411 | | 0.0003 | 881.0 | 153294 | 0.6343 | 0.7683 | 0.7920 | 0.7800 | 0.9406 | | 0.0003 | 882.0 | 153468 | 0.6101 | 0.7520 | 0.7895 | 0.7703 | 0.9387 | | 0.0005 | 883.0 | 153642 | 0.6241 | 0.7665 | 0.7898 | 0.7780 | 0.9406 | | 0.0005 | 884.0 | 153816 | 0.6413 | 0.7677 | 0.7934 | 0.7804 | 0.9408 | | 0.0005 | 885.0 | 153990 | 0.6446 | 0.7592 | 0.7956 | 0.7770 | 0.9408 | | 0.0002 | 886.0 | 154164 | 0.6245 | 0.7623 | 0.7897 | 0.7758 | 0.9399 | | 0.0002 | 887.0 | 154338 | 0.6366 | 0.7666 | 0.7967 | 0.7813 | 0.9407 | | 0.0003 | 888.0 | 154512 | 0.6413 | 0.7628 | 0.7942 | 0.7782 | 0.9403 | | 0.0003 | 889.0 | 154686 | 0.6300 | 0.7632 | 0.7990 | 0.7807 | 0.9409 | | 0.0003 | 890.0 | 154860 | 0.6219 | 0.7640 | 0.7956 | 0.7795 | 0.9400 | | 0.0004 | 891.0 | 155034 | 0.6225 | 0.7647 | 0.7891 | 0.7767 | 0.9399 | | 0.0004 | 892.0 | 155208 | 0.6477 | 0.7662 | 0.7816 | 0.7738 | 0.9395 | | 0.0004 | 893.0 | 155382 | 0.6345 | 0.7694 | 0.7873 | 0.7783 | 0.9403 | | 0.0004 | 894.0 | 155556 | 0.5839 | 0.7660 | 0.7931 | 0.7793 | 0.9402 | | 0.0004 | 895.0 | 155730 | 0.6053 | 0.7579 | 0.7999 | 0.7783 | 0.9398 | | 0.0004 | 896.0 | 155904 | 0.5843 | 0.7707 | 0.7834 | 0.7770 | 0.9401 | | 0.0005 | 897.0 | 156078 | 0.6095 | 0.7651 | 0.7938 | 0.7792 | 0.9392 | | 0.0005 | 898.0 | 156252 | 0.6045 | 0.7640 | 0.7958 | 0.7796 | 0.9406 | | 0.0005 | 899.0 | 156426 | 0.6185 | 0.7625 | 0.7943 | 0.7781 | 0.9399 | | 0.0004 | 900.0 | 156600 | 0.6091 | 0.7636 | 0.7900 | 0.7766 | 0.9401 | | 0.0004 | 901.0 | 156774 | 0.6223 | 0.7673 | 0.7906 | 0.7788 | 0.9405 | | 0.0004 | 902.0 | 156948 | 0.6251 | 0.7681 | 0.7927 | 0.7802 | 0.9417 | | 0.0003 | 903.0 | 157122 | 0.6235 | 0.7657 | 0.7882 | 0.7768 | 0.9409 | | 0.0003 | 904.0 | 157296 | 0.6192 | 0.7749 | 0.7958 | 0.7852 | 0.9417 | | 0.0003 | 905.0 | 157470 | 0.6311 | 0.7724 | 0.7897 | 0.7809 | 0.9405 | | 0.0002 | 906.0 | 157644 | 0.6373 | 0.7669 | 0.7967 | 0.7815 | 0.9419 | | 0.0002 | 907.0 | 157818 | 0.6306 | 0.7643 | 0.7990 | 0.7813 | 0.9412 | | 0.0002 | 908.0 | 157992 | 0.6225 | 0.7703 | 0.7945 | 0.7822 | 0.9412 | | 0.0002 | 909.0 | 158166 | 0.6268 | 0.7733 | 0.7967 | 0.7848 | 0.9421 | | 0.0002 | 910.0 | 158340 | 0.6422 | 0.7759 | 0.7994 | 0.7875 | 0.9421 | | 0.0002 | 911.0 | 158514 | 0.6512 | 0.7676 | 0.8041 | 0.7854 | 0.9422 | | 0.0002 | 912.0 | 158688 | 0.6567 | 0.7701 | 0.8012 | 0.7853 | 0.9420 | | 0.0002 | 913.0 | 158862 | 0.6555 | 0.7672 | 0.7999 | 0.7832 | 0.9419 | | 0.0002 | 914.0 | 159036 | 0.6499 | 0.7679 | 0.7978 | 0.7825 | 0.9416 | | 0.0002 | 915.0 | 159210 | 0.6461 | 0.7659 | 0.7990 | 0.7821 | 0.9416 | | 0.0002 | 916.0 | 159384 | 0.6302 | 0.7701 | 0.7909 | 0.7804 | 0.9413 | | 0.0003 | 917.0 | 159558 | 0.6350 | 0.7665 | 0.7916 | 0.7789 | 0.9412 | | 0.0003 | 918.0 | 159732 | 0.6447 | 0.7647 | 0.7940 | 0.7790 | 0.9413 | | 0.0003 | 919.0 | 159906 | 0.6557 | 0.7666 | 0.7954 | 0.7807 | 0.9416 | | 0.0001 | 920.0 | 160080 | 0.6554 | 0.7714 | 0.7954 | 0.7832 | 0.9417 | | 0.0001 | 921.0 | 160254 | 0.6628 | 0.7657 | 0.7852 | 0.7753 | 0.9403 | | 0.0001 | 922.0 | 160428 | 0.6537 | 0.7687 | 0.7826 | 0.7756 | 0.9407 | | 0.0002 | 923.0 | 160602 | 0.6584 | 0.7642 | 0.7925 | 0.7781 | 0.9410 | | 0.0002 | 924.0 | 160776 | 0.6516 | 0.7715 | 0.7965 | 0.7838 | 0.9414 | | 0.0002 | 925.0 | 160950 | 0.6378 | 0.7691 | 0.7978 | 0.7832 | 0.9417 | | 0.0003 | 926.0 | 161124 | 0.6408 | 0.7716 | 0.7934 | 0.7824 | 0.9407 | | 0.0003 | 927.0 | 161298 | 0.6366 | 0.7717 | 0.7895 | 0.7805 | 0.9408 | | 0.0003 | 928.0 | 161472 | 0.6325 | 0.7678 | 0.7983 | 0.7827 | 0.9410 | | 0.0002 | 929.0 | 161646 | 0.6356 | 0.7723 | 0.7940 | 0.7830 | 0.9411 | | 0.0002 | 930.0 | 161820 | 0.6340 | 0.7723 | 0.7981 | 0.7850 | 0.9414 | | 0.0002 | 931.0 | 161994 | 0.6349 | 0.7755 | 0.7981 | 0.7867 | 0.9417 | | 0.0002 | 932.0 | 162168 | 0.6261 | 0.7783 | 0.7913 | 0.7847 | 0.9416 | | 0.0002 | 933.0 | 162342 | 0.6299 | 0.7783 | 0.7940 | 0.7861 | 0.9421 | | 0.0001 | 934.0 | 162516 | 0.6277 | 0.7767 | 0.7911 | 0.7838 | 0.9411 | | 0.0001 | 935.0 | 162690 | 0.6299 | 0.7733 | 0.7949 | 0.7839 | 0.9409 | | 0.0001 | 936.0 | 162864 | 0.6429 | 0.7705 | 0.7967 | 0.7834 | 0.9406 | | 0.0001 | 937.0 | 163038 | 0.6487 | 0.7734 | 0.7958 | 0.7844 | 0.9408 | | 0.0001 | 938.0 | 163212 | 0.6485 | 0.7729 | 0.7925 | 0.7826 | 0.9408 | | 0.0001 | 939.0 | 163386 | 0.6593 | 0.7687 | 0.7967 | 0.7825 | 0.9409 | | 0.0002 | 940.0 | 163560 | 0.6535 | 0.7674 | 0.7960 | 0.7814 | 0.9404 | | 0.0002 | 941.0 | 163734 | 0.6542 | 0.7684 | 0.8046 | 0.7861 | 0.9414 | | 0.0002 | 942.0 | 163908 | 0.6575 | 0.77 | 0.8042 | 0.7868 | 0.9418 | | 0.0001 | 943.0 | 164082 | 0.6625 | 0.7725 | 0.7969 | 0.7845 | 0.9415 | | 0.0001 | 944.0 | 164256 | 0.6729 | 0.7747 | 0.7961 | 0.7853 | 0.9412 | | 0.0001 | 945.0 | 164430 | 0.6757 | 0.7729 | 0.7956 | 0.7841 | 0.9416 | | 0.0002 | 946.0 | 164604 | 0.6629 | 0.7720 | 0.8014 | 0.7864 | 0.9417 | | 0.0002 | 947.0 | 164778 | 0.6645 | 0.7737 | 0.7999 | 0.7866 | 0.9420 | | 0.0002 | 948.0 | 164952 | 0.6658 | 0.7777 | 0.7902 | 0.7839 | 0.9416 | | 0.0001 | 949.0 | 165126 | 0.6666 | 0.7790 | 0.7933 | 0.7860 | 0.9421 | | 0.0001 | 950.0 | 165300 | 0.6737 | 0.7688 | 0.8062 | 0.7871 | 0.9422 | | 0.0001 | 951.0 | 165474 | 0.6776 | 0.7723 | 0.8046 | 0.7881 | 0.9424 | | 0.0002 | 952.0 | 165648 | 0.6628 | 0.7735 | 0.7976 | 0.7854 | 0.9422 | | 0.0002 | 953.0 | 165822 | 0.6619 | 0.7773 | 0.7918 | 0.7845 | 0.9414 | | 0.0002 | 954.0 | 165996 | 0.6516 | 0.7765 | 0.7978 | 0.7870 | 0.9421 | | 0.0002 | 955.0 | 166170 | 0.6534 | 0.7714 | 0.8003 | 0.7856 | 0.9420 | | 0.0002 | 956.0 | 166344 | 0.6476 | 0.7754 | 0.7999 | 0.7874 | 0.9421 | | 0.0003 | 957.0 | 166518 | 0.6444 | 0.7745 | 0.7974 | 0.7858 | 0.9417 | | 0.0003 | 958.0 | 166692 | 0.6442 | 0.7754 | 0.7985 | 0.7868 | 0.9418 | | 0.0003 | 959.0 | 166866 | 0.6619 | 0.7704 | 0.7976 | 0.7838 | 0.9409 | | 0.0002 | 960.0 | 167040 | 0.6678 | 0.7732 | 0.7987 | 0.7857 | 0.9413 | | 0.0002 | 961.0 | 167214 | 0.6673 | 0.7758 | 0.8003 | 0.7879 | 0.9417 | | 0.0002 | 962.0 | 167388 | 0.6671 | 0.7749 | 0.8023 | 0.7884 | 0.9417 | | 0.0001 | 963.0 | 167562 | 0.6559 | 0.7718 | 0.8019 | 0.7865 | 0.9415 | | 0.0001 | 964.0 | 167736 | 0.6596 | 0.7728 | 0.7976 | 0.7850 | 0.9412 | | 0.0001 | 965.0 | 167910 | 0.6554 | 0.7714 | 0.8028 | 0.7868 | 0.9418 | | 0.0002 | 966.0 | 168084 | 0.6524 | 0.7716 | 0.8026 | 0.7868 | 0.9418 | | 0.0002 | 967.0 | 168258 | 0.6546 | 0.7715 | 0.8019 | 0.7864 | 0.9416 | | 0.0002 | 968.0 | 168432 | 0.6555 | 0.7708 | 0.8024 | 0.7863 | 0.9419 | | 0.0001 | 969.0 | 168606 | 0.6524 | 0.7708 | 0.7990 | 0.7847 | 0.9418 | | 0.0001 | 970.0 | 168780 | 0.6575 | 0.7697 | 0.7999 | 0.7845 | 0.9416 | | 0.0001 | 971.0 | 168954 | 0.6583 | 0.7732 | 0.7996 | 0.7862 | 0.9418 | | 0.0001 | 972.0 | 169128 | 0.6571 | 0.7717 | 0.8021 | 0.7866 | 0.9419 | | 0.0001 | 973.0 | 169302 | 0.6606 | 0.7725 | 0.7985 | 0.7853 | 0.9417 | | 0.0001 | 974.0 | 169476 | 0.6600 | 0.7718 | 0.8010 | 0.7861 | 0.9421 | | 0.0001 | 975.0 | 169650 | 0.6629 | 0.7705 | 0.8046 | 0.7872 | 0.9422 | | 0.0001 | 976.0 | 169824 | 0.6607 | 0.7732 | 0.8014 | 0.7871 | 0.9422 | | 0.0001 | 977.0 | 169998 | 0.6619 | 0.7728 | 0.7987 | 0.7855 | 0.9418 | | 0.0001 | 978.0 | 170172 | 0.6641 | 0.7715 | 0.8019 | 0.7864 | 0.9421 | | 0.0001 | 979.0 | 170346 | 0.6599 | 0.7708 | 0.8001 | 0.7852 | 0.9419 | | 0.0001 | 980.0 | 170520 | 0.6615 | 0.7721 | 0.8028 | 0.7871 | 0.9420 | | 0.0001 | 981.0 | 170694 | 0.6620 | 0.7729 | 0.8033 | 0.7878 | 0.9421 | | 0.0001 | 982.0 | 170868 | 0.6630 | 0.7725 | 0.8015 | 0.7867 | 0.9421 | | 0.0001 | 983.0 | 171042 | 0.6621 | 0.7738 | 0.7976 | 0.7855 | 0.9418 | | 0.0001 | 984.0 | 171216 | 0.6634 | 0.7733 | 0.7979 | 0.7854 | 0.9417 | | 0.0001 | 985.0 | 171390 | 0.6642 | 0.7741 | 0.8008 | 0.7872 | 0.9417 | | 0.0001 | 986.0 | 171564 | 0.6660 | 0.7713 | 0.8030 | 0.7868 | 0.9418 | | 0.0001 | 987.0 | 171738 | 0.6668 | 0.7717 | 0.8030 | 0.7870 | 0.9418 | | 0.0001 | 988.0 | 171912 | 0.6639 | 0.7717 | 0.7987 | 0.7850 | 0.9415 | | 0.0 | 989.0 | 172086 | 0.6646 | 0.7720 | 0.7983 | 0.7849 | 0.9416 | | 0.0 | 990.0 | 172260 | 0.6626 | 0.7745 | 0.7983 | 0.7862 | 0.9417 | | 0.0 | 991.0 | 172434 | 0.6630 | 0.7740 | 0.7981 | 0.7859 | 0.9417 | | 0.0001 | 992.0 | 172608 | 0.6630 | 0.7733 | 0.7978 | 0.7853 | 0.9417 | | 0.0001 | 993.0 | 172782 | 0.6607 | 0.7746 | 0.7988 | 0.7865 | 0.9418 | | 0.0001 | 994.0 | 172956 | 0.6612 | 0.7750 | 0.7996 | 0.7871 | 0.9418 | | 0.0001 | 995.0 | 173130 | 0.6608 | 0.7749 | 0.7992 | 0.7869 | 0.9419 | | 0.0001 | 996.0 | 173304 | 0.6601 | 0.7748 | 0.7988 | 0.7867 | 0.9418 | | 0.0001 | 997.0 | 173478 | 0.6604 | 0.7743 | 0.7988 | 0.7864 | 0.9418 | | 0.0 | 998.0 | 173652 | 0.6605 | 0.7751 | 0.7999 | 0.7873 | 0.9419 | | 0.0 | 999.0 | 173826 | 0.6606 | 0.7753 | 0.8003 | 0.7876 | 0.9420 | | 0.0003 | 1000.0 | 174000 | 0.6607 | 0.7753 | 0.8003 | 0.7876 | 0.9420 | ### Framework versions - Transformers 4.29.2 - Pytorch 2.0.1+cu117 - Datasets 2.12.0 - Tokenizers 0.13.3
bibuwei1/bloom_prompt_tuning_1696929687.587977
bibuwei1
2023-10-10T09:27:37Z
2
0
peft
[ "peft", "region:us" ]
null
2023-10-10T09:27:34Z
--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.4.0
ayeshaliaqat/ppo-LunarLander-v2
ayeshaliaqat
2023-10-10T09:25:06Z
1
0
stable-baselines3
[ "stable-baselines3", "LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T09:24:50Z
--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: -325.31 +/- 84.40 name: mean_reward verified: false --- # **PPO** Agent playing **LunarLander-v2** This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```
abheek19/q-FrozenLake-v1-4x4-noSlippery
abheek19
2023-10-10T09:25:06Z
0
0
null
[ "FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T09:25:04Z
--- tags: - FrozenLake-v1-4x4-no_slippery - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-FrozenLake-v1-4x4-noSlippery results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: FrozenLake-v1-4x4-no_slippery type: FrozenLake-v1-4x4-no_slippery metrics: - type: mean_reward value: 1.00 +/- 0.00 name: mean_reward verified: false --- # **Q-Learning** Agent playing1 **FrozenLake-v1** This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** . ## Usage ```python model = load_from_hub(repo_id="abheek19/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
diwank/dfe-large-en-2
diwank
2023-10-10T08:57:48Z
8
0
sentence-transformers
[ "sentence-transformers", "pytorch", "bert", "feature-extraction", "sentence-similarity", "autotrain_compatible", "text-embeddings-inference", "endpoints_compatible", "region:us" ]
sentence-similarity
2023-10-10T08:57:31Z
--- pipeline_tag: sentence-similarity tags: - sentence-transformers - feature-extraction - sentence-similarity --- # diwank/dfe-large-en-2 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 2048 dimensional dense vector space and can be used for tasks like clustering or semantic search. <!--- Describe your model here --> ## Usage (Sentence-Transformers) Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed: ``` pip install -U sentence-transformers ``` Then you can use the model like this: ```python from sentence_transformers import SentenceTransformer sentences = ["This is an example sentence", "Each sentence is converted"] model = SentenceTransformer('diwank/dfe-large-en-2') embeddings = model.encode(sentences) print(embeddings) ``` ## Evaluation Results <!--- Describe how your model was evaluated --> For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=diwank/dfe-large-en-2) ## Training The model was trained with the parameters: **DataLoader**: `torch.utils.data.dataloader.DataLoader` of length 3633 with parameters: ``` {'batch_size': 1024, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'} ``` **Loss**: `sentence_transformers.losses.CosineSimilarityLoss.CosineSimilarityLoss` Parameters of the fit()-Method: ``` { "epochs": 4, "evaluation_steps": 2000, "evaluator": "sentence_transformers.evaluation.EmbeddingSimilarityEvaluator.EmbeddingSimilarityEvaluator", "max_grad_norm": 1, "optimizer_class": "<class 'lion_pytorch.lion_pytorch.Lion'>", "optimizer_params": { "lr": 0.0001, "weight_decay": 0.01 }, "scheduler": "WarmupCosine", "steps_per_epoch": null, "warmup_steps": 100, "weight_decay": 0.01 } ``` ## Full Model Architecture ``` SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': True}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False}) (2): Asym( (dialog-0): Dense({'in_features': 1024, 'out_features': 2048, 'bias': True, 'activation_function': 'torch.nn.modules.activation.Tanh'}) (dialog-1): Dense({'in_features': 2048, 'out_features': 2048, 'bias': True, 'activation_function': 'torch.nn.modules.activation.Tanh'}) (dialog-2): Dropout( (dropout_layer): Dropout(p=0.1, inplace=False) ) (dialog-3): Dense({'in_features': 2048, 'out_features': 2048, 'bias': True, 'activation_function': 'torch.nn.modules.activation.Tanh'}) (dialog-4): Dense({'in_features': 2048, 'out_features': 1024, 'bias': True, 'activation_function': 'torch.nn.modules.activation.Tanh'}) (dialog-5): Normalize() (fact-0): Dense({'in_features': 1024, 'out_features': 2048, 'bias': True, 'activation_function': 'torch.nn.modules.activation.Tanh'}) (fact-1): Dense({'in_features': 2048, 'out_features': 2048, 'bias': True, 'activation_function': 'torch.nn.modules.activation.Tanh'}) (fact-2): Dropout( (dropout_layer): Dropout(p=0.1, inplace=False) ) (fact-3): Dense({'in_features': 2048, 'out_features': 2048, 'bias': True, 'activation_function': 'torch.nn.modules.activation.Tanh'}) (fact-4): Dense({'in_features': 2048, 'out_features': 1024, 'bias': True, 'activation_function': 'torch.nn.modules.activation.Tanh'}) (fact-5): Normalize() ) ) ``` ## Citing & Authors <!--- Describe where people can find more information -->
XiaohaiZhu/a2c-PandaReachDense-v3
XiaohaiZhu
2023-10-10T08:47:35Z
0
0
stable-baselines3
[ "stable-baselines3", "PandaReachDense-v3", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T08:37:24Z
--- library_name: stable-baselines3 tags: - PandaReachDense-v3 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: A2C results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: PandaReachDense-v3 type: PandaReachDense-v3 metrics: - type: mean_reward value: -0.24 +/- 0.15 name: mean_reward verified: false --- # **A2C** Agent playing **PandaReachDense-v3** This is a trained model of a **A2C** agent playing **PandaReachDense-v3** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```
HaseebArshad786/LunarLander
HaseebArshad786
2023-10-10T08:47:11Z
0
0
stable-baselines3
[ "stable-baselines3", "LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]
reinforcement-learning
2023-10-09T20:34:30Z
--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: 268.40 +/- 21.70 name: mean_reward verified: false --- # **PPO** Agent playing **LunarLander-v2** This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```
User1115/whisper-large-v2-hindi-100steps
User1115
2023-10-10T08:46:45Z
1
0
peft
[ "peft", "arxiv:1910.09700", "base_model:openai/whisper-large-v2", "base_model:adapter:openai/whisper-large-v2", "region:us" ]
null
2023-09-29T17:28:55Z
--- library_name: peft base_model: openai/whisper-large-v2 --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Data Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ## Training procedure The following `bitsandbytes` quantization config was used during training: - quant_method: bitsandbytes - load_in_8bit: True - load_in_4bit: False - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: fp4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float32 ### Framework versions - PEFT 0.6.0.dev0
alperenunlu/poca-SoccerTwos
alperenunlu
2023-10-10T08:44:41Z
41
2
ml-agents
[ "ml-agents", "tensorboard", "onnx", "SoccerTwos", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SoccerTwos", "region:us" ]
reinforcement-learning
2023-10-10T08:38:06Z
--- library_name: ml-agents tags: - SoccerTwos - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SoccerTwos --- # **poca** Agent playing **SoccerTwos** This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/ We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: - A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction - A *longer tutorial* to understand how works ML-Agents: https://huggingface.co/learn/deep-rl-course/unit5/introduction ### Resume the training ```bash mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume ``` ### Watch your Agent play You can watch your agent **playing directly in your browser** 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity 2. Step 1: Find your model_id: alperenunlu/poca-SoccerTwos 3. Step 2: Select your *.nn /*.onnx file 4. Click on Watch the agent play 👀
flax-community/t5-base-cnn-dm
flax-community
2023-10-10T08:42:55Z
423
1
transformers
[ "transformers", "pytorch", "jax", "tensorboard", "safetensors", "t5", "text2text-generation", "summarization", "en", "dataset:cnn_dailymail", "license:apache-2.0", "model-index", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]
summarization
2022-03-02T23:29:05Z
--- language: en license: apache-2.0 tags: - summarization datasets: - cnn_dailymail model-index: - name: flax-community/t5-base-cnn-dm results: - task: type: summarization name: Summarization dataset: name: cnn_dailymail type: cnn_dailymail config: 3.0.0 split: test metrics: - type: rouge value: 24.1585 name: ROUGE-1 verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiN2Q0Nzk3ZTNkNTFjMTM2YjliNzcxYTVlMDgyNDE4MzZjNzgzZjgzYjI1NWFjZTE2YjE4MWE3NGRiNGZiMmVhNyIsInZlcnNpb24iOjF9.H2oS1cN5A3wY8oFZTVtCMwnbDPAdUhNwjTSDocqQinhDq7aSee_AvIVn-7m84Ke8qaMTAvHB9e56MDAAVT8XBA - type: rouge value: 11.0688 name: ROUGE-2 verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZGIyMmYzZTFhNjgwMmU5YWQ1MTZjM2ZlNjEwYmVmODkyMGQwZDQ2MjM1YmRkYjM2NTEyNjE5N2ExYzc0ZTcyYSIsInZlcnNpb24iOjF9.6GtmrXTD0EnrXx02enbLdbeiLh--I9u0GfrPdXZ_CKHeYgpFs0Gk1F0c75QBfGoMilodGymS15A9Bjvt00baBw - type: rouge value: 19.7293 name: ROUGE-L verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzc4MGQyNmYwNDk5NDE0MDk2ZjE2NmVkZDIwN2NmYzQxZTI0NWZhZjkxOGFkMWZmNjQ5NzRkODViNzg5Zjc5MiIsInZlcnNpb24iOjF9.rOgFJeHsW74nQiKc3DPoMIB9aWKqWTRtnweYP3DCp4duJN5jq32PPNyXo3EYuskGgTSp4KWwf7-Hl2MYwDrSCQ - type: rouge value: 22.6394 name: ROUGE-LSUM verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTA4M2JlZDliMmFlZDgwM2E2MDZjY2ZjZGUwZTcxNDM0NGU3NzdlYzJlZTEzNDEyZDE0OWFiMjUzMmYwNjRhNyIsInZlcnNpb24iOjF9.Mq9ltLQ5YAZfLLaGsPtSOe6KCRLRwjT_2nSAH9KWvOiyagJ16F5xQ1m9uUx9mhiu_UOmpjDaAtD3y4AOy4L0Dg - type: loss value: 2.516355514526367 name: loss verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOGQwNTIyZmU5ZjU3OWM1NGMwYzJiYTA0ZGVmOTA2MjcxYzZmZDRjZDViZDg0NGNlOWNjODkxYTc1ZTJhMmYyMiIsInZlcnNpb24iOjF9.mh6ZVu82CFnb5g92Uj-99wjyvoSQQI-gO-PDBdH4JZyc8mVPJYzV-S7jyXwC_XsOfD1OsR9XKTxM1NUirfBKAw - type: gen_len value: 18.9993 name: gen_len verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGY5YTYxZmZiYmY4NTZjNmMzMjllNWE1M2M2ZjA0MWM1MzBhZjc0MDM5ZGFiYTAzNjFiZjg5ZjMxYzlmOGYwMyIsInZlcnNpb24iOjF9.eXiPrQ-CeB3BWzlQzkTIA1q0xYP1GtFGIK9XyIneEmh5ajN5pCATxNDvn6n09d84OEr5432SoPJfdpNCd_UyCA --- # Model This model is fine-tuned from https://huggingface.co/flax-community/t5-base-openwebtext, fine-tuned on cnn_dailymail.
JJJJerry/Taxi-v3
JJJJerry
2023-10-10T08:40:24Z
0
0
null
[ "Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T08:40:21Z
--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: Taxi-v3 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 metrics: - type: mean_reward value: 7.54 +/- 2.72 name: mean_reward verified: false --- # **Q-Learning** Agent playing1 **Taxi-v3** This is a trained model of a **Q-Learning** agent playing **Taxi-v3** . ## Usage ```python model = load_from_hub(repo_id="JJJJerry/Taxi-v3", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
Gayathri142214002/Pegasus_paraphraser_ComQG_3
Gayathri142214002
2023-10-10T08:37:28Z
3
0
transformers
[ "transformers", "pytorch", "pegasus", "text2text-generation", "generated_from_trainer", "autotrain_compatible", "endpoints_compatible", "region:us" ]
text2text-generation
2023-10-10T06:44:44Z
--- tags: - generated_from_trainer model-index: - name: Pegasus_paraphraser_ComQG_3 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Pegasus_paraphraser_ComQG_3 This model is a fine-tuned version of [Gayathri142214002/Pegasus_paraphraser_ComQG_2](https://huggingface.co/Gayathri142214002/Pegasus_paraphraser_ComQG_2) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.2753 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 1 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.2237 | 0.47 | 1000 | 0.2237 | | 0.244 | 0.93 | 2000 | 0.2321 | | 0.2073 | 1.4 | 3000 | 0.2543 | | 0.213 | 1.86 | 4000 | 0.2511 | | 0.1863 | 2.33 | 5000 | 0.2712 | | 0.1844 | 2.79 | 6000 | 0.2621 | | 0.1707 | 3.26 | 7000 | 0.2778 | | 0.1585 | 3.72 | 8000 | 0.2753 | ### Framework versions - Transformers 4.29.2 - Pytorch 2.0.1+cu117 - Datasets 2.12.0 - Tokenizers 0.13.3
JJJJerry/q-FrozenLake-v1-4x4-noSlippery
JJJJerry
2023-10-10T08:36:34Z
0
0
null
[ "FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T08:36:31Z
--- tags: - FrozenLake-v1-4x4-no_slippery - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-FrozenLake-v1-4x4-noSlippery results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: FrozenLake-v1-4x4-no_slippery type: FrozenLake-v1-4x4-no_slippery metrics: - type: mean_reward value: 1.00 +/- 0.00 name: mean_reward verified: false --- # **Q-Learning** Agent playing1 **FrozenLake-v1** This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** . ## Usage ```python model = load_from_hub(repo_id="JJJJerry/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
SHENMU007/neunit_BASE_V9.5.15
SHENMU007
2023-10-10T08:32:33Z
77
0
transformers
[ "transformers", "pytorch", "speecht5", "text-to-audio", "1.1.0", "generated_from_trainer", "zh", "dataset:facebook/voxpopuli", "base_model:microsoft/speecht5_tts", "base_model:finetune:microsoft/speecht5_tts", "license:mit", "endpoints_compatible", "region:us" ]
text-to-audio
2023-10-10T07:29:20Z
--- language: - zh license: mit base_model: microsoft/speecht5_tts tags: - 1.1.0 - generated_from_trainer datasets: - facebook/voxpopuli model-index: - name: SpeechT5 TTS Dutch neunit results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # SpeechT5 TTS Dutch neunit This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the VoxPopuli dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 4000 ### Training results ### Framework versions - Transformers 4.33.1 - Pytorch 2.0.1+cu117 - Datasets 2.14.5 - Tokenizers 0.13.3
DopeorNope/zerocoka7_adpt
DopeorNope
2023-10-10T08:26:42Z
2
0
peft
[ "peft", "pytorch", "region:us" ]
null
2023-10-10T08:26:19Z
--- library_name: peft --- ## Training procedure The following `bitsandbytes` quantization config was used during training: - load_in_8bit: True - load_in_4bit: False - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: fp4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float32 ### Framework versions - PEFT 0.5.0.dev0
Yousefmd/arabert-emotions-classification
Yousefmd
2023-10-10T08:13:38Z
34
1
transformers
[ "transformers", "pytorch", "tensorboard", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-large-arabertv02", "base_model:finetune:aubmindlab/bert-large-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]
text-classification
2023-06-22T18:58:32Z
--- base_model: aubmindlab/bert-large-arabertv02 tags: - generated_from_trainer metrics: - f1 - accuracy model-index: - name: arabert-emotions-classification results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # arabert-emotions-classification This model is a fine-tuned version of [aubmindlab/bert-large-arabertv02](https://huggingface.co/aubmindlab/bert-large-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2817 - F1: 0.7006 - Roc Auc: 0.7931 - Accuracy: 0.2769 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 20 - eval_batch_size: 20 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| | No log | 1.0 | 190 | 0.3665 | 0.5604 | 0.7049 | 0.1761 | | No log | 2.0 | 380 | 0.3086 | 0.6755 | 0.7775 | 0.2564 | | 0.3831 | 3.0 | 570 | 0.2953 | 0.6848 | 0.7812 | 0.2496 | | 0.3831 | 4.0 | 760 | 0.2849 | 0.6933 | 0.7866 | 0.2615 | | 0.3831 | 5.0 | 950 | 0.2817 | 0.7006 | 0.7931 | 0.2769 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1
STomoya/vit_small_patch16_224.st_safebooru_1k
STomoya
2023-10-10T08:11:50Z
15
0
timm
[ "timm", "pytorch", "safetensors", "image-classification", "license:apache-2.0", "region:us" ]
image-classification
2023-10-08T11:22:23Z
--- tags: - image-classification - timm library_name: timm license: apache-2.0 --- # Model card for vit_small_patch16_224.st_safebooru_1k ## Model Details - **metrics:** |Precision|Recall|F1-score| |-|-|-| |0.7959206109368223|0.3983023195703428|0.5058713479582103|
JackCloudman/tora-code-34b-v1.0-GGUF
JackCloudman
2023-10-10T08:06:22Z
2
2
transformers
[ "transformers", "gguf", "code", "math", "text-generation", "en", "dataset:gsm8k", "dataset:competition_math", "arxiv:2309.17452", "license:llama2", "endpoints_compatible", "region:us" ]
text-generation
2023-10-10T07:20:03Z
--- license: llama2 datasets: - gsm8k - competition_math language: - en metrics: - exact_match library_name: transformers pipeline_tag: text-generation tags: - code - math --- <h1 align="center">⚠️Testing Quantized Tora-Code-34b-v1.0 GGUF⚠️</h1> <hr> <p>Original README</p> <h1 align="center"> ToRA: A Tool-Integrated Reasoning Agent <br> for Mathematical Problem Solving </h1> <p align="center"> <a href="https://microsoft.github.io/ToRA/"><b>[🌐 Website]</b></a> • <a href="https://arxiv.org/pdf/2309.17452.pdf"><b>[📜 Paper]</b></a> • <a href="https://huggingface.co/llm-agents"><b>[🤗 HF Models]</b></a> • <a href="https://github.com/microsoft/ToRA"><b>[🐱 GitHub]</b></a> <br> <a href="https://twitter.com/zhs05232838/status/1708860992631763092"><b>[🐦 Twitter]</b></a> • <a href="https://www.reddit.com/r/LocalLLaMA/comments/1703k6d/tora_a_toolintegrated_reasoning_agent_for/"><b>[💬 Reddit]</b></a> • <a href="https://notes.aimodels.fyi/researchers-announce-tora-training-language-models-to-better-understand-math-using-external-tools/">[🍀 Unofficial Blog]</a> <!-- <a href="#-quick-start">Quick Start</a> • --> <!-- <a href="#%EF%B8%8F-citation">Citation</a> --> </p> <p align="center"> Repo for "<a href="https://arxiv.org/pdf/2309.17452.pdf" target="_blank">ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving</a>" </p> ## 🔥 News - [2023/10/08] 🔥🔥🔥 All ToRA models released at [HuggingFace](https://huggingface.co/llm-agents)!!! - [2023/09/29] ToRA paper, repo, and website released. ## 💡 Introduction ToRA is a series of Tool-integrated Reasoning Agents designed to solve challenging mathematical reasoning problems by interacting with tools, e.g., computation libraries and symbolic solvers. ToRA series seamlessly integrate natural language reasoning with the utilization of external tools, thereby amalgamating the analytical prowess of language and the computational efficiency of external tools. | Model | Size | GSM8k | MATH | AVG@10 math tasks<sup>&dagger;</sup> | |---|---|---|---|---| | GPT-4 | - | 92.0 | 42.5 | 78.3 | | GPT-4 (PAL) | - | 94.2 | 51.8 | 86.4 | | [ToRA-7B](https://huggingface.co/llm-agents/tora-7b-v1.0) | 7B | 68.8 | 40.1 | 62.4| | [ToRA-Code-7B](https://huggingface.co/llm-agents/tora-code-7b-v1.0) | 7B | 72.6 | 44.6 | 66.5| | [ToRA-13B](https://huggingface.co/llm-agents/tora-13b-v1.0) | 13B | 72.7 | 43.0 | 65.9| | [ToRA-Code-13B](https://huggingface.co/llm-agents/tora-code-13b-v1.0) | 13B | 75.8 | 48.1 | 71.3 | | [ToRA-Code-34B<sup>*</sup>](https://huggingface.co/llm-agents/tora-code-34b-v1.0) | 34B | 80.7 | **51.0** | 74.8 | | [ToRA-70B](https://huggingface.co/llm-agents/tora-70b-v1.0) | 70B | **84.3** | 49.7 | **76.9** | - <sup>*</sup>ToRA-Code-34B is currently the first and only open-source model to achieve over 50% accuracy (pass@1) on the MATH dataset, which significantly outperforms GPT-4’s CoT result (51.0 vs. 42.5), and is competitive with GPT-4 solving problems with programs. By open-sourcing our codes and models, we hope more breakthroughs will come! - <sup>&dagger;</sup>10 math tasks include GSM8k, MATH, GSM-Hard, SVAMP, TabMWP, ASDiv, SingleEQ, SingleOP, AddSub, and MultiArith. ## ⚡️ Training The models are trained on ToRA-Corpus 16k, which contains tool-integrated reasoning trajectories of MATH and GSM8k from GPT-4. We use imitation learning (i.e., SFT) to fine-tune the models, and then apply our proposed *output space shaping* to improve tool-integrated reasoning behaviors. Please refer to the [paper](https://arxiv.org/pdf/2309.17452.pdf) for more details. ## 🪁 Inference & Evaluation Please refer to ToRA's [GitHub repo](https://github.com/microsoft/ToRA) for inference, evaluation, and training code. ## ☕️ Citation If you find this repository helpful, please consider citing our paper: ``` @misc{gou2023tora, title={ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving}, author={Zhibin Gou and Zhihong Shao and Yeyun Gong and yelong shen and Yujiu Yang and Minlie Huang and Nan Duan and Weizhu Chen}, year={2023}, eprint={2309.17452}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```
not-tanh/ppo-LunarLander-v2
not-tanh
2023-10-10T07:47:36Z
0
0
stable-baselines3
[ "stable-baselines3", "LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T07:09:12Z
--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: 256.61 +/- 24.12 name: mean_reward verified: false --- # **PPO** Agent playing **LunarLander-v2** This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```
MattStammers/appo-atari_choppercommand
MattStammers
2023-10-10T07:47:26Z
0
0
sample-factory
[ "sample-factory", "tensorboard", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]
reinforcement-learning
2023-09-25T23:52:42Z
--- library_name: sample-factory tags: - deep-reinforcement-learning - reinforcement-learning - sample-factory model-index: - name: APPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: atari_choppercommand type: atari_choppercommand metrics: - type: mean_reward value: 35570.00 +/- 17871.60 name: mean_reward verified: false --- A(n) **APPO** model trained on the **atari_choppercommand** environment. This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory. Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/ ## Downloading the model After installing Sample-Factory, download the model with: ``` python -m sample_factory.huggingface.load_from_hub -r MattStammers/APPO-atari_choppercommand ``` ## About the Model This model as with all the others in the benchmarks was trained initially asynchronously un-seeded to 10 million steps for the purposes of setting a sample factory async baseline for this model on this environment but only 3/57 made it. The aim is to reach state-of-the-art (SOTA) performance on each atari environment. I will flag the models with SOTA when they reach at or near these levels. The hyperparameters used in the model are the ones I have pushed to my fork of sample-factory: https://github.com/MattStammers/sample-factory. Given that https://huggingface.co/edbeeching has kindly shared his. I saved time and energy by using many of his tuned hyperparameters to maximise performance. However, he used 2 billion training steps. I have started as explained above at 10 million then moved to 100m to see how performance goes: ``` hyperparameters = { "device": "gpu", "seed": 1234, "num_policies": 2, "async_rl": true, "serial_mode": false, "batched_sampling": true, "num_batches_to_accumulate": 2, "worker_num_splits": 1, "policy_workers_per_policy": 1, "max_policy_lag": 1000, "num_workers": 16, "num_envs_per_worker": 2, "batch_size": 1024, "num_batches_per_epoch": 8, "num_epochs": 4, "rollout": 128, "recurrence": 1, "shuffle_minibatches": false, "gamma": 0.99, "reward_scale": 1.0, "reward_clip": 1000.0, "value_bootstrap": false, "normalize_returns": true, "exploration_loss_coeff": 0.0004677351413, "value_loss_coeff": 0.5, "kl_loss_coeff": 0.0, "exploration_loss": "entropy", "gae_lambda": 0.95, "ppo_clip_ratio": 0.1, "ppo_clip_value": 1.0, "with_vtrace": false, "vtrace_rho": 1.0, "vtrace_c": 1.0, "optimizer": "adam", "adam_eps": 1e-05, "adam_beta1": 0.9, "adam_beta2": 0.999, "max_grad_norm": 0.0, "learning_rate": 0.0003033891184, "lr_schedule": "linear_decay", "lr_schedule_kl_threshold": 0.008, "lr_adaptive_min": 1e-06, "lr_adaptive_max": 0.01, "obs_subtract_mean": 0.0, "obs_scale": 255.0, "normalize_input": true, "normalize_input_keys": [ "obs" ], "decorrelate_experience_max_seconds": 0, "decorrelate_envs_on_one_worker": true, "actor_worker_gpus": [], "set_workers_cpu_affinity": true, "force_envs_single_thread": false, "default_niceness": 0, "log_to_file": true, "experiment_summaries_interval": 3, "flush_summaries_interval": 30, "stats_avg": 100, "summaries_use_frameskip": true, "heartbeat_interval": 10, "heartbeat_reporting_interval": 60, "train_for_env_steps": 100000000, "train_for_seconds": 10000000000, "save_every_sec": 120, "keep_checkpoints": 2, "load_checkpoint_kind": "latest", "save_milestones_sec": 1200, "save_best_every_sec": 5, "save_best_metric": "reward", "save_best_after": 100000, "benchmark": false, "encoder_mlp_layers": [ 512, 512 ], "encoder_conv_architecture": "convnet_atari", "encoder_conv_mlp_layers": [ 512 ], "use_rnn": false, "rnn_size": 512, "rnn_type": "gru", "rnn_num_layers": 1, "decoder_mlp_layers": [], "nonlinearity": "relu", "policy_initialization": "orthogonal", "policy_init_gain": 1.0, "actor_critic_share_weights": true, "adaptive_stddev": false, "continuous_tanh_scale": 0.0, "initial_stddev": 1.0, "use_env_info_cache": false, "env_gpu_actions": false, "env_gpu_observations": true, "env_frameskip": 4, "env_framestack": 4, } ``` ## Using the model To run the model after download, use the `enjoy` script corresponding to this environment: ``` python -m sf_examples.atari.enjoy_atari --algo=APPO --env=atari_choppercommand --train_dir=./train_dir --experiment=APPO-atari_choppercommand ``` You can also upload models to the Hugging Face Hub using the same script with the `--push_to_hub` flag. See https://www.samplefactory.dev/10-huggingface/huggingface/ for more details ## Training with this model To continue training with this model, use the `train` script corresponding to this environment: ``` python -m sf_examples.atari.train_atari --algo=APPO --env=atari_choppercommand --train_dir=./train_dir --experiment=APPO-atari_choppercommand --restart_behavior=resume --train_for_env_steps=10000000000 ``` Note, you may have to adjust `--train_for_env_steps` to a suitably high number as the experiment will resume at the number of steps it concluded at.
kporzycki/a2c-PandaReachDense-v3
kporzycki
2023-10-10T07:44:49Z
0
0
stable-baselines3
[ "stable-baselines3", "PandaReachDense-v3", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T07:39:15Z
--- library_name: stable-baselines3 tags: - PandaReachDense-v3 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: A2C results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: PandaReachDense-v3 type: PandaReachDense-v3 metrics: - type: mean_reward value: -0.24 +/- 0.11 name: mean_reward verified: false --- # **A2C** Agent playing **PandaReachDense-v3** This is a trained model of a **A2C** agent playing **PandaReachDense-v3** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```
AdiOO7/Azure-Classifier-dolly-7B
AdiOO7
2023-10-10T07:42:30Z
2
0
peft
[ "peft", "arxiv:1910.09700", "base_model:diegi97/dolly-v2-6.9b-sharded-bf16", "base_model:adapter:diegi97/dolly-v2-6.9b-sharded-bf16", "region:us" ]
null
2023-10-10T07:42:25Z
--- library_name: peft base_model: diegi97/dolly-v2-6.9b-sharded-bf16 --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Data Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ## Training procedure The following `bitsandbytes` quantization config was used during training: - quant_method: bitsandbytes - load_in_8bit: False - load_in_4bit: True - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: nf4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: bfloat16 ### Framework versions - PEFT 0.6.0.dev0
SniiKz/Phi_1_Phase1
SniiKz
2023-10-10T07:37:29Z
56
0
transformers
[ "transformers", "pytorch", "mixformer-sequential", "text-generation", "generated_from_trainer", "custom_code", "base_model:microsoft/phi-1_5", "base_model:finetune:microsoft/phi-1_5", "license:other", "autotrain_compatible", "region:us" ]
text-generation
2023-10-10T06:58:28Z
--- license: other base_model: microsoft/phi-1_5 tags: - generated_from_trainer model-index: - name: Phi_1_Phase1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Phi_1_Phase1 This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the None dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - training_steps: 1000 ### Training results ### Framework versions - Transformers 4.34.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1
DLimited/em_mistral
DLimited
2023-10-10T07:32:26Z
0
0
null
[ "gguf", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
2023-10-09T12:45:09Z
--- license: apache-2.0 --- unquantized .gguf for https://huggingface.co/jphme/em_german_mistral_v01
suoluo/ddpm-celebahq-finetuned-butterflies-2epochs
suoluo
2023-10-10T07:32:11Z
44
0
diffusers
[ "diffusers", "safetensors", "pytorch", "unconditional-image-generation", "diffusion-models-class", "license:mit", "diffusers:DDPMPipeline", "region:us" ]
unconditional-image-generation
2023-10-10T07:30:49Z
--- license: mit tags: - pytorch - diffusers - unconditional-image-generation - diffusion-models-class --- # Example Fine-Tuned Model for Unit 2 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class) Describe your model here ## Usage ```python from diffusers import DDPMPipeline pipeline = DDPMPipeline.from_pretrained('suoluo/ddpm-celebahq-finetuned-butterflies-2epochs') image = pipeline().images[0] image ```
jurikuehn/mistral-finetuned-samsum
jurikuehn
2023-10-10T07:28:14Z
0
0
null
[ "generated_from_trainer", "base_model:TheBloke/Mistral-7B-Instruct-v0.1-GPTQ", "base_model:finetune:TheBloke/Mistral-7B-Instruct-v0.1-GPTQ", "license:apache-2.0", "region:us" ]
null
2023-10-09T08:00:01Z
--- license: apache-2.0 base_model: TheBloke/Mistral-7B-Instruct-v0.1-GPTQ tags: - generated_from_trainer model-index: - name: mistral-finetuned-samsum results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # mistral-finetuned-samsum This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.1-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GPTQ) on the None dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - training_steps: 250 ### Training results ### Framework versions - Transformers 4.34.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1
promptora11/llama
promptora11
2023-10-10T07:13:15Z
10
0
transformers
[ "transformers", "pytorch", "safetensors", "llama", "text-generation", "facebook", "meta", "llama-2", "en", "arxiv:2307.09288", "autotrain_compatible", "text-generation-inference", "region:us" ]
text-generation
2023-10-10T06:48:17Z
--- extra_gated_heading: Access Llama 2 on Hugging Face extra_gated_description: >- This is a form to enable access to Llama 2 on Hugging Face after you have been granted access from Meta. Please visit the [Meta website](https://ai.meta.com/resources/models-and-libraries/llama-downloads) and accept our license terms and acceptable use policy before submitting this form. Requests will be processed in 1-2 days. extra_gated_prompt: "**Your Hugging Face account email address MUST match the email you provide on the Meta website, or your request will not be approved.**" extra_gated_button_content: Submit extra_gated_fields: I agree to share my name, email address and username with Meta and confirm that I have already been granted download access on the Meta website: checkbox language: - en pipeline_tag: text-generation inference: false arxiv: 2307.09288 tags: - facebook - meta - pytorch - llama - llama-2 --- # **Llama 2** Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the repository for the 7B fine-tuned model, optimized for dialogue use cases and converted for the Hugging Face Transformers format. Links to other models can be found in the index at the bottom. ## Model Details *Note: Use of this model is governed by the Meta license. In order to download the model weights and tokenizer, please visit the [website](https://ai.meta.com/resources/models-and-libraries/llama-downloads/) and accept our License before requesting access here.* Meta developed and publicly released the Llama 2 family of large language models (LLMs), a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. Our fine-tuned LLMs, called Llama-2-Chat, are optimized for dialogue use cases. Llama-2-Chat models outperform open-source chat models on most benchmarks we tested, and in our human evaluations for helpfulness and safety, are on par with some popular closed-source models like ChatGPT and PaLM. **Model Developers** Meta **Variations** Llama 2 comes in a range of parameter sizes — 7B, 13B, and 70B — as well as pretrained and fine-tuned variations. **Input** Models input text only. **Output** Models generate text only. **Model Architecture** Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align to human preferences for helpfulness and safety. ||Training Data|Params|Content Length|GQA|Tokens|LR| |---|---|---|---|---|---|---| |Llama 2|*A new mix of publicly available online data*|7B|4k|&#10007;|2.0T|3.0 x 10<sup>-4</sup>| |Llama 2|*A new mix of publicly available online data*|13B|4k|&#10007;|2.0T|3.0 x 10<sup>-4</sup>| |Llama 2|*A new mix of publicly available online data*|70B|4k|&#10004;|2.0T|1.5 x 10<sup>-4</sup>| *Llama 2 family of models.* Token counts refer to pretraining data only. All models are trained with a global batch-size of 4M tokens. Bigger models - 70B -- use Grouped-Query Attention (GQA) for improved inference scalability. **Model Dates** Llama 2 was trained between January 2023 and July 2023. **Status** This is a static model trained on an offline dataset. Future versions of the tuned models will be released as we improve model safety with community feedback. **License** A custom commercial license is available at: [https://ai.meta.com/resources/models-and-libraries/llama-downloads/](https://ai.meta.com/resources/models-and-libraries/llama-downloads/) **Research Paper** ["Llama-2: Open Foundation and Fine-tuned Chat Models"](arxiv.org/abs/2307.09288) ## Intended Use **Intended Use Cases** Llama 2 is intended for commercial and research use in English. Tuned models are intended for assistant-like chat, whereas pretrained models can be adapted for a variety of natural language generation tasks. To get the expected features and performance for the chat versions, a specific formatting needs to be followed, including the `INST` and `<<SYS>>` tags, `BOS` and `EOS` tokens, and the whitespaces and breaklines in between (we recommend calling `strip()` on inputs to avoid double-spaces). See our reference code in github for details: [`chat_completion`](https://github.com/facebookresearch/llama/blob/main/llama/generation.py#L212). **Out-of-scope Uses** Use in any manner that violates applicable laws or regulations (including trade compliance laws).Use in languages other than English. Use in any other way that is prohibited by the Acceptable Use Policy and Licensing Agreement for Llama 2. ## Hardware and Software **Training Factors** We used custom training libraries, Meta's Research Super Cluster, and production clusters for pretraining. Fine-tuning, annotation, and evaluation were also performed on third-party cloud compute. **Carbon Footprint** Pretraining utilized a cumulative 3.3M GPU hours of computation on hardware of type A100-80GB (TDP of 350-400W). Estimated total emissions were 539 tCO2eq, 100% of which were offset by Meta’s sustainability program. ||Time (GPU hours)|Power Consumption (W)|Carbon Emitted(tCO<sub>2</sub>eq)| |---|---|---|---| |Llama 2 7B|184320|400|31.22| |Llama 2 13B|368640|400|62.44| |Llama 2 70B|1720320|400|291.42| |Total|3311616||539.00| **CO<sub>2</sub> emissions during pretraining.** Time: total GPU time required for training each model. Power Consumption: peak power capacity per GPU device for the GPUs used adjusted for power usage efficiency. 100% of the emissions are directly offset by Meta's sustainability program, and because we are openly releasing these models, the pretraining costs do not need to be incurred by others. ## Training Data **Overview** Llama 2 was pretrained on 2 trillion tokens of data from publicly available sources. The fine-tuning data includes publicly available instruction datasets, as well as over one million new human-annotated examples. Neither the pretraining nor the fine-tuning datasets include Meta user data. **Data Freshness** The pretraining data has a cutoff of September 2022, but some tuning data is more recent, up to July 2023. ## Evaluation Results In this section, we report the results for the Llama 1 and Llama 2 models on standard academic benchmarks.For all the evaluations, we use our internal evaluations library. |Model|Size|Code|Commonsense Reasoning|World Knowledge|Reading Comprehension|Math|MMLU|BBH|AGI Eval| |---|---|---|---|---|---|---|---|---|---| |Llama 1|7B|14.1|60.8|46.2|58.5|6.95|35.1|30.3|23.9| |Llama 1|13B|18.9|66.1|52.6|62.3|10.9|46.9|37.0|33.9| |Llama 1|33B|26.0|70.0|58.4|67.6|21.4|57.8|39.8|41.7| |Llama 1|65B|30.7|70.7|60.5|68.6|30.8|63.4|43.5|47.6| |Llama 2|7B|16.8|63.9|48.9|61.3|14.6|45.3|32.6|29.3| |Llama 2|13B|24.5|66.9|55.4|65.8|28.7|54.8|39.4|39.1| |Llama 2|70B|**37.5**|**71.9**|**63.6**|**69.4**|**35.2**|**68.9**|**51.2**|**54.2**| **Overall performance on grouped academic benchmarks.** *Code:* We report the average pass@1 scores of our models on HumanEval and MBPP. *Commonsense Reasoning:* We report the average of PIQA, SIQA, HellaSwag, WinoGrande, ARC easy and challenge, OpenBookQA, and CommonsenseQA. We report 7-shot results for CommonSenseQA and 0-shot results for all other benchmarks. *World Knowledge:* We evaluate the 5-shot performance on NaturalQuestions and TriviaQA and report the average. *Reading Comprehension:* For reading comprehension, we report the 0-shot average on SQuAD, QuAC, and BoolQ. *MATH:* We report the average of the GSM8K (8 shot) and MATH (4 shot) benchmarks at top 1. |||TruthfulQA|Toxigen| |---|---|---|---| |Llama 1|7B|27.42|23.00| |Llama 1|13B|41.74|23.08| |Llama 1|33B|44.19|22.57| |Llama 1|65B|48.71|21.77| |Llama 2|7B|33.29|**21.25**| |Llama 2|13B|41.86|26.10| |Llama 2|70B|**50.18**|24.60| **Evaluation of pretrained LLMs on automatic safety benchmarks.** For TruthfulQA, we present the percentage of generations that are both truthful and informative (the higher the better). For ToxiGen, we present the percentage of toxic generations (the smaller the better). |||TruthfulQA|Toxigen| |---|---|---|---| |Llama-2-Chat|7B|57.04|**0.00**| |Llama-2-Chat|13B|62.18|**0.00**| |Llama-2-Chat|70B|**64.14**|0.01| **Evaluation of fine-tuned LLMs on different safety datasets.** Same metric definitions as above. ## Ethical Considerations and Limitations Llama 2 is a new technology that carries risks with use. Testing conducted to date has been in English, and has not covered, nor could it cover all scenarios. For these reasons, as with all LLMs, Llama 2’s potential outputs cannot be predicted in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses to user prompts. Therefore, before deploying any applications of Llama 2, developers should perform safety testing and tuning tailored to their specific applications of the model. Please see the Responsible Use Guide available at [https://ai.meta.com/llama/responsible-use-guide/](https://ai.meta.com/llama/responsible-use-guide) ## Reporting Issues Please report any software “bug,” or other problems with the models through one of the following means: - Reporting issues with the model: [github.com/facebookresearch/llama](http://github.com/facebookresearch/llama) - Reporting problematic content generated by the model: [developers.facebook.com/llama_output_feedback](http://developers.facebook.com/llama_output_feedback) - Reporting bugs and security concerns: [facebook.com/whitehat/info](http://facebook.com/whitehat/info) ## Llama Model Index |Model|Llama2|Llama2-hf|Llama2-chat|Llama2-chat-hf| |---|---|---|---|---| |7B| [Link](https://huggingface.co/llamaste/Llama-2-7b) | [Link](https://huggingface.co/llamaste/Llama-2-7b-hf) | [Link](https://huggingface.co/llamaste/Llama-2-7b-chat) | [Link](https://huggingface.co/llamaste/Llama-2-7b-chat-hf)| |13B| [Link](https://huggingface.co/llamaste/Llama-2-13b) | [Link](https://huggingface.co/llamaste/Llama-2-13b-hf) | [Link](https://huggingface.co/llamaste/Llama-2-13b-chat) | [Link](https://huggingface.co/llamaste/Llama-2-13b-hf)| |70B| [Link](https://huggingface.co/llamaste/Llama-2-70b) | [Link](https://huggingface.co/llamaste/Llama-2-70b-hf) | [Link](https://huggingface.co/llamaste/Llama-2-70b-chat) | [Link](https://huggingface.co/llamaste/Llama-2-70b-hf)|
hyeju/sdxl-bird-emoji
hyeju
2023-10-10T07:04:43Z
5
0
diffusers
[ "diffusers", "tensorboard", "stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "lora", "base_model:stabilityai/stable-diffusion-xl-base-1.0", "base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0", "license:openrail++", "region:us" ]
text-to-image
2023-10-10T05:24:30Z
--- license: openrail++ base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: a emoji of sks bird tags: - stable-diffusion-xl - stable-diffusion-xl-diffusers - text-to-image - diffusers - lora inference: true --- # LoRA DreamBooth - hyeju/sdxl-bird-emoji These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were trained on a emoji of sks bird using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following. LoRA for the text encoder was enabled: False. Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
spacy/ca_core_news_lg
spacy
2023-10-10T06:54:22Z
14
2
spacy
[ "spacy", "token-classification", "ca", "license:gpl-3.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - ca license: gpl-3.0 model-index: - name: ca_core_news_lg results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8481469334 - name: NER Recall type: recall value: 0.8366224523 - name: NER F Score type: f_score value: 0.8423452769 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9846920735 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9846920735 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9818721217 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9805595069 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.9176385395 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8876925862 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9906377999 --- ### Details: https://spacy.io/models/ca#ca_core_news_lg Catalan pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer. | Feature | Description | | --- | --- | | **Name** | `ca_core_news_lg` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` | | **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) | | **Sources** | [UD Catalan AnCora v2.8](https://github.com/UniversalDependencies/UD_Catalan-AnCora) (Martínez Alonso, Héctor; Pascual, Elena; Zeman, Daniel)<br />[UD Catalan AnCora v2.8 + NER v3.2.9](https://github.com/TeMU-BSC/spacy/releases/tag/3.2.9) (Carlos Rodríguez-Penagos and Carme Armentano-Oller)<br />[Catalan Lemmatizer](https://github.com/explosion/spacy-lookups-data) (Text Mining Unit, Barcelona Supercomputing Center)<br />[Catalan Word Embeddings in FastText (Version 1.0)](http://doi.org/10.5281/zenodo.4522041) (Gutiérrez-Fandiño, Asier, Armengol-Estapé, Jordi, Gonzalez-Agirre, Aitor, Carrino, Casimiro Pio, de Gibert, Ona, & Villegas, Marta) | | **License** | `GNU GPL 3.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (317 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `POS=PROPN`, `POS=PUNCT\|PunctSide=Ini\|PunctType=Brck`, `POS=PUNCT\|PunctSide=Fin\|PunctType=Brck`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Fem\|Number=Sing\|POS=NOUN`, `POS=ADP`, `NumType=Card\|Number=Plur\|POS=NUM`, `Gender=Masc\|Number=Plur\|POS=NOUN`, `Number=Sing\|POS=ADJ`, `POS=CCONJ`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `NumForm=Digit\|NumType=Card\|POS=NUM`, `NumForm=Digit\|POS=NOUN`, `Gender=Masc\|Number=Plur\|POS=ADJ`, `POS=PUNCT\|PunctType=Comm`, `POS=AUX\|VerbForm=Inf`, `Case=Acc,Dat\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `POS=PRON\|PronType=Rel`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Fem\|Number=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Gender=Fem\|Number=Plur\|POS=NOUN`, `Gender=Fem\|Number=Plur\|POS=ADJ`, `POS=VERB\|VerbForm=Inf`, `Case=Acc,Dat\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Plur\|POS=ADJ`, `POS=PUNCT\|PunctType=Peri`, `Number=Sing\|POS=PRON\|PronType=Rel`, `Gender=Masc\|Number=Sing\|POS=NOUN`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part`, `POS=SCONJ`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Definite=Def\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `POS=VERB\|VerbForm=Ger`, `POS=NOUN`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Gender=Fem\|NumType=Ord\|Number=Plur\|POS=ADJ`, `POS=SYM`, `Gender=Masc\|Number=Sing\|POS=ADJ`, `Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `POS=ADV\|Polarity=Neg`, `POS=ADV`, `Number=Sing\|POS=PRON\|PronType=Dem`, `Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Number=Plur\|POS=NOUN`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=ADJ`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Tot`, `Case=Loc\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Fem\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Degree=Cmp\|POS=ADV`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Gender=Fem\|Number=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Gender=Masc\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `NumType=Card\|POS=NUM`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Number=Sing\|POS=PRON\|PronType=Ind`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Number=Plur\|POS=DET\|PronType=Ind`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Sing\|POS=DET\|PronType=Ind`, `POS=PUNCT`, `Number=Sing\|POS=DET\|PronType=Rel`, `Case=Gen\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `POS=DET\|PronType=Ind`, `POS=AUX`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc,Dat\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Degree=Cmp\|Number=Sing\|POS=ADJ`, `Number=Sing\|POS=VERB`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Ind`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem,Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Ind`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Ind`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|PronType=Rel`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `AdvType=Tim\|POS=NOUN`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=3\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Int`, `POS=PUNCT\|PunctType=Semi`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=3\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Ind`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `NumForm=Digit\|POS=SYM`, `Gender=Masc\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Int`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `POS=PRON\|PronType=Int`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin`, `POS=PART`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Dem`, `POS=ADJ`, `Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Degree=Cmp\|Number=Plur\|POS=ADJ`, `POS=PUNCT\|PunctType=Dash`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `POS=SPACE`, `Gender=Fem\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|POS=NOUN`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Int`, `Gender=Masc\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Fut\|VerbForm=Fin`, `POS=PUNCT\|PunctType=Colo`, `Gender=Masc\|NumType=Card\|POS=NUM`, `Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Sing\|POS=PRON\|PronType=Int`, `POS=PUNCT\|PunctType=Quot`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `POS=AUX\|VerbForm=Ger`, `Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Imp\|Number=Sing\|POS=AUX\|Person=3\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|PronType=Ind`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Acc,Dat\|Number=Sing\|POS=PRON\|Person=2\|Polite=Infm\|PrepCase=Npr\|PronType=Prs`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Int`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `NumForm=Digit\|NumType=Frac\|POS=NUM`, `POS=VERB`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Dem`, `Gender=Fem\|POS=NOUN`, `Case=Acc,Dat\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Fut\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=2\|Polite=Infm\|PronType=Prs`, `POS=X`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=1\|VerbForm=Fin`, `Number=Sing\|POS=DET\|PronType=Dem`, `POS=DET`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `NumType=Ord\|Number=Sing\|POS=ADJ`, `Gender=Fem\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part`, `Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Gender=Fem\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Part`, `Gender=Masc\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Part`, `Number=Plur\|POS=PRON\|PronType=Dem`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin`, `POS=PRON\|PronType=Ind`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Pre\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `POS=PUNCT\|PunctSide=Fin\|PunctType=Qest`, `NumForm=Digit\|NumType=Ord\|POS=ADJ`, `Case=Acc\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Reflex=Yes`, `NumForm=Digit\|NumType=Frac\|POS=SYM`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `POS=PUNCT\|PunctSide=Ini\|PunctType=Qest`, `NumType=Card\|Number=Sing\|POS=NUM`, `Foreign=Yes\|POS=PRON\|PronType=Int`, `Foreign=Yes\|Mood=Ind\|POS=VERB\|VerbForm=Fin`, `Foreign=Yes\|POS=ADP`, `Gender=Masc\|Number=Sing\|POS=PROPN`, `POS=PUNCT\|PunctSide=Ini\|PunctType=Excl`, `POS=PUNCT\|PunctSide=Fin\|PunctType=Excl`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=1\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=2\|Polite=Form\|PronType=Prs`, `Mood=Sub\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `POS=PUNCT\|PunctSide=Ini\|PunctType=Comm`, `POS=PUNCT\|PunctSide=Fin\|PunctType=Comm`, `Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Acc,Dat\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Number=Sing\|POS=PRON\|Person=2\|Polite=Form\|PronType=Prs`, `Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `POS=VERB\|Tense=Past\|VerbForm=Part`, `Mood=Imp\|Number=Plur\|POS=AUX\|Person=3\|VerbForm=Fin`, `Case=Nom\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Rel`, `Definite=Ind\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Number=Plur\|Number[psor]=Plur\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `POS=AUX\|Tense=Past\|VerbForm=Part`, `Gender=Fem\|NumType=Card\|POS=NUM`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `AdvType=Tim\|Degree=Cmp\|POS=ADV`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|Polite=Infm\|PrepCase=Pre\|PronType=Prs`, `POS=DET\|PronType=Rel`, `Definite=Ind\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Fut\|VerbForm=Fin`, `POS=INTJ`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `POS=VERB\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Foreign=Yes\|POS=NOUN`, `Foreign=Yes\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Foreign=Yes\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Foreign=Yes\|POS=SCONJ`, `Foreign=Yes\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|POS=SYM`, `Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Number=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Gender=Fem\|Number=Sing\|POS=PROPN`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Definite=Def\|Foreign=Yes\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Foreign=Yes\|POS=VERB`, `Foreign=Yes\|POS=ADJ`, `Foreign=Yes\|POS=DET`, `Foreign=Yes\|POS=ADV`, `POS=PUNCT\|PunctSide=Fin\|Punta d'aignctType=Brck`, `Degree=Cmp\|POS=ADJ`, `AdvType=Tim\|POS=SYM`, `Number=Plur\|POS=DET\|PronType=Dem`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Fut\|VerbForm=Fin` | | **`parser`** | `ROOT`, `acl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `case`, `cc`, `ccomp`, `compound`, `conj`, `cop`, `csubj`, `dep`, `det`, `expl:pass`, `fixed`, `flat`, `iobj`, `mark`, `nmod`, `nsubj`, `nummod`, `obj`, `obl`, `parataxis`, `punct`, `xcomp` | | **`ner`** | `LOC`, `MISC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.93 | | `TOKEN_P` | 99.78 | | `TOKEN_R` | 99.79 | | `TOKEN_F` | 99.79 | | `POS_ACC` | 98.47 | | `MORPH_ACC` | 98.19 | | `MORPH_MICRO_P` | 99.56 | | `MORPH_MICRO_R` | 99.05 | | `MORPH_MICRO_F` | 99.30 | | `SENTS_P` | 99.06 | | `SENTS_R` | 99.06 | | `SENTS_F` | 99.06 | | `DEP_UAS` | 91.76 | | `DEP_LAS` | 88.77 | | `TAG_ACC` | 98.47 | | `LEMMA_ACC` | 98.06 | | `ENTS_P` | 84.81 | | `ENTS_R` | 83.66 | | `ENTS_F` | 84.23 |
spacy/da_core_news_lg
spacy
2023-10-10T06:53:27Z
21
0
spacy
[ "spacy", "token-classification", "da", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - da license: cc-by-sa-4.0 model-index: - name: da_core_news_lg results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.800407332 - name: NER Recall type: recall value: 0.81875 - name: NER F Score type: f_score value: 0.8094747683 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9665859564 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9665859564 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9573849879 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.948377724 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8225238813 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.7828612927 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.8869100623 --- ### Details: https://spacy.io/models/da#da_core_news_lg Danish pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner, attribute_ruler. | Feature | Description | | --- | --- | | **Name** | `da_core_news_lg` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) | | **Sources** | [UD Danish DDT v2.8](https://github.com/UniversalDependencies/UD_Danish-DDT) (Johannsen, Anders; Martínez Alonso, Héctor; Plank, Barbara)<br />[DaNE](https://github.com/alexandrainst/danlp/blob/master/docs/datasets.md#danish-dependency-treebank-dane) (Rasmus Hvingelby, Amalie B. Pauli, Maria Barrett, Christina Rosted, Lasse M. Lidegaard, Anders Søgaard)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (194 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `AdpType=Prep\|POS=ADP`, `Definite=Ind\|Gender=Com\|Number=Sing\|POS=NOUN`, `Mood=Ind\|POS=AUX\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `POS=PROPN`, `Definite=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Definite=Def\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=SCONJ`, `Definite=Def\|Gender=Com\|Number=Sing\|POS=NOUN`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `POS=ADV`, `Number=Plur\|POS=DET\|PronType=Dem`, `Degree=Pos\|Number=Plur\|POS=ADJ`, `Definite=Ind\|Gender=Com\|Number=Plur\|POS=NOUN`, `POS=PUNCT`, `POS=CCONJ`, `Definite=Ind\|Degree=Cmp\|Number=Sing\|POS=ADJ`, `Degree=Cmp\|POS=ADJ`, `POS=PRON\|PartType=Inf`, `Gender=Com\|Number=Sing\|POS=DET\|PronType=Ind`, `Definite=Ind\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Definite=Ind\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Definite=Def\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Degree=Pos\|POS=ADV`, `Definite=Def\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=PRON\|PronType=Dem`, `NumType=Card\|POS=NUM`, `Definite=Ind\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Com\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Degree=Pos\|Gender=Com\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Com\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `NumType=Ord\|POS=ADJ`, `Gender=Com\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Mood=Ind\|POS=AUX\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `POS=VERB\|VerbForm=Inf\|Voice=Act`, `Mood=Ind\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `POS=NOUN`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `POS=ADP\|PartType=Inf`, `Degree=Pos\|POS=ADJ`, `Definite=Def\|Gender=Com\|Number=Plur\|POS=NOUN`, `Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Def\|Gender=Com\|Number=Sing\|POS=NOUN`, `POS=AUX\|VerbForm=Inf\|Voice=Act`, `Definite=Ind\|Degree=Pos\|Gender=Com\|Number=Sing\|POS=ADJ`, `Gender=Com\|Number=Sing\|POS=DET\|PronType=Dem`, `Number=Plur\|POS=DET\|PronType=Ind`, `Gender=Com\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Acc\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `POS=PART\|PartType=Inf`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Gender=Com\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Gender=Com\|POS=PRON\|PronType=Ind`, `Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Mood=Imp\|POS=VERB`, `Gender=Com\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Definite=Ind\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part`, `POS=X`, `Case=Nom\|Gender=Com\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Definite=Def\|Gender=Com\|Number=Plur\|POS=NOUN`, `POS=VERB\|Tense=Pres\|VerbForm=Part`, `Number=Plur\|POS=PRON\|PronType=Int,Rel`, `POS=VERB\|VerbForm=Inf\|Voice=Pass`, `Case=Gen\|Definite=Ind\|Gender=Com\|Number=Sing\|POS=NOUN`, `Degree=Cmp\|POS=ADV`, `POS=ADV\|PartType=Inf`, `Degree=Sup\|POS=ADV`, `Number=Plur\|POS=PRON\|PronType=Dem`, `Number=Plur\|POS=PRON\|PronType=Ind`, `Definite=Def\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Com\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|POS=PROPN`, `POS=ADP`, `Degree=Cmp\|Number=Plur\|POS=ADJ`, `Definite=Def\|Degree=Sup\|POS=ADJ`, `Gender=Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Degree=Pos\|Number=Sing\|POS=ADJ`, `Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Gender=Com\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs\|Style=Form`, `Number=Plur\|POS=PRON\|PronType=Rcp`, `Case=Gen\|Degree=Cmp\|POS=ADJ`, `POS=SPACE`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=INTJ`, `Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs\|Style=Form`, `Case=Acc\|Gender=Com\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Gender=Com\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Ind\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Number=Sing\|POS=PRON\|PronType=Int,Rel`, `Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs\|Style=Form`, `Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Int,Rel`, `Definite=Def\|Degree=Sup\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Com\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Gender=Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Definite=Ind\|Number=Sing\|POS=NOUN`, `Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Number=Plur\|Number[psor]=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `POS=SYM`, `Case=Nom\|Gender=Com\|POS=PRON\|Person=2\|Polite=Form\|PronType=Prs`, `Degree=Sup\|POS=ADJ`, `Number=Plur\|POS=DET\|PronType=Ind\|Style=Arch`, `Case=Gen\|Gender=Com\|Number=Sing\|POS=DET\|PronType=Dem`, `Foreign=Yes\|POS=X`, `POS=DET\|Person=2\|Polite=Form\|Poss=Yes\|PronType=Prs`, `Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Acc\|Gender=Com\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|POS=PRON\|PronType=Int,Rel`, `Gender=Com\|Number=Sing\|POS=PRON\|PronType=Dem`, `Abbr=Yes\|POS=X`, `Case=Gen\|Definite=Ind\|Gender=Com\|Number=Plur\|POS=NOUN`, `Definite=Def\|Degree=Abs\|POS=ADJ`, `Definite=Ind\|Degree=Sup\|Number=Sing\|POS=ADJ`, `Definite=Ind\|POS=NOUN`, `Gender=Com\|Number=Plur\|POS=NOUN`, `Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Gender=Com\|POS=PRON\|PronType=Int,Rel`, `Case=Nom\|Gender=Com\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Degree=Abs\|POS=ADV`, `POS=VERB\|VerbForm=Ger`, `POS=VERB\|Tense=Past\|VerbForm=Part`, `Definite=Def\|Degree=Sup\|Number=Sing\|POS=ADJ`, `Number=Plur\|Number[psor]=Plur\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs\|Style=Form`, `Case=Gen\|Definite=Def\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Com\|POS=PRON\|Person=2\|Polite=Form\|PronType=Prs`, `Gender=Com\|Number=Sing\|POS=PRON\|PronType=Int,Rel`, `POS=VERB\|Tense=Pres`, `Case=Gen\|Number=Plur\|POS=DET\|PronType=Ind`, `Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `POS=PRON\|Person=2\|Polite=Form\|Poss=Yes\|PronType=Prs`, `Gender=Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `POS=AUX\|Tense=Pres\|VerbForm=Part`, `Mood=Ind\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Gender=Com\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Degree=Sup\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Com\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Gender=Neut\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Definite=Ind\|Number=Plur\|POS=NOUN`, `Case=Gen\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Mood=Imp\|POS=AUX`, `Gender=Com\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Number[psor]=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Definite=Def\|Gender=Com\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Com\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Gen\|POS=NOUN`, `Number[psor]=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=DET\|PronType=Dem`, `Definite=Def\|Number=Plur\|POS=NOUN` | | **`parser`** | `ROOT`, `acl:relcl`, `advcl`, `advmod`, `advmod:lmod`, `amod`, `appos`, `aux`, `case`, `cc`, `ccomp`, `compound:prt`, `conj`, `cop`, `dep`, `det`, `expl`, `fixed`, `flat`, `iobj`, `list`, `mark`, `nmod`, `nmod:poss`, `nsubj`, `nummod`, `obj`, `obl`, `obl:lmod`, `obl:tmod`, `punct`, `xcomp` | | **`ner`** | `LOC`, `MISC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.89 | | `TOKEN_P` | 99.78 | | `TOKEN_R` | 99.75 | | `TOKEN_F` | 99.76 | | `POS_ACC` | 96.66 | | `MORPH_ACC` | 95.74 | | `MORPH_MICRO_P` | 97.43 | | `MORPH_MICRO_R` | 96.75 | | `MORPH_MICRO_F` | 97.09 | | `SENTS_P` | 89.09 | | `SENTS_R` | 88.30 | | `SENTS_F` | 88.69 | | `DEP_UAS` | 82.25 | | `DEP_LAS` | 78.29 | | `LEMMA_ACC` | 94.84 | | `TAG_ACC` | 96.66 | | `ENTS_P` | 80.04 | | `ENTS_R` | 81.88 | | `ENTS_F` | 80.95 |
spacy/de_core_news_lg
spacy
2023-10-10T06:52:34Z
24
0
spacy
[ "spacy", "token-classification", "de", "license:mit", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - de license: mit model-index: - name: de_core_news_lg results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8527131783 - name: NER Recall type: recall value: 0.844401557 - name: NER F Score type: f_score value: 0.8485370145 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9795559667 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9841217399 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9205894013 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9790945371 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.9265658098 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.9078030166 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9541230945 --- ### Details: https://spacy.io/models/de#de_core_news_lg German pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner. | Feature | Description | | --- | --- | | **Name** | `de_core_news_lg` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) | | **Sources** | [TIGER Corpus](https://www.ims.uni-stuttgart.de/forschung/ressourcen/korpora/tiger.html) (Brants, Sabine, Stefanie Dipper, Peter Eisenberg, Silvia Hansen, Esther König, Wolfgang Lezius, Christian Rohrer, George Smith, and Hans Uszkoreit)<br />[Tiger2Dep](https://www.ims.uni-stuttgart.de/forschung/ressourcen/werkzeuge/tiger2dep/) (Wolfgang Seeker)<br />[WikiNER](https://figshare.com/articles/Learning_multilingual_named_entity_recognition_from_Wikipedia/5462500) (Joel Nothman, Nicky Ringland, Will Radford, Tara Murphy, James R Curran)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `MIT` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (772 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `$(`, `$,`, `$.`, `ADJA`, `ADJD`, `ADV`, `APPO`, `APPR`, `APPRART`, `APZR`, `ART`, `CARD`, `FM`, `ITJ`, `KOKOM`, `KON`, `KOUI`, `KOUS`, `NE`, `NN`, `NNE`, `PDAT`, `PDS`, `PIAT`, `PIS`, `PPER`, `PPOSAT`, `PPOSS`, `PRELAT`, `PRELS`, `PRF`, `PROAV`, `PTKA`, `PTKANT`, `PTKNEG`, `PTKVZ`, `PTKZU`, `PWAT`, `PWAV`, `PWS`, `TRUNC`, `VAFIN`, `VAIMP`, `VAINF`, `VAPP`, `VMFIN`, `VMINF`, `VMPP`, `VVFIN`, `VVIMP`, `VVINF`, `VVIZU`, `VVPP`, `XY`, `_SP` | | **`morphologizer`** | `POS=PUNCT`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `POS=ADV`, `Case=Nom\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=ADP`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PROPN`, `POS=VERB\|VerbForm=Part`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Foreign=Yes\|POS=X`, `Degree=Pos\|POS=ADV`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=ADP`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Dat\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Dat\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Dat\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=CCONJ`, `POS=SCONJ`, `Case=Acc\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `POS=VERB\|VerbForm=Inf`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Acc\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=NOUN`, `POS=PART`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Dat\|Definite=Def\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Dat\|Number=Plur\|POS=PROPN`, `POS=PRON\|PronType=Ind`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Dat\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Sing\|POS=PROPN`, `Case=Dat\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=NOUN`, `POS=NUM`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=ADP`, `Gender=Neut\|POS=NOUN`, `Case=Acc\|Number=Sing\|POS=PROPN`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Gen\|Definite=Def\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Definite=Def\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `POS=PROPN`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `POS=INTJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Rel`, `Gender=Masc\|POS=NOUN`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `POS=SCONJ\|PronType=Int`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Dat\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Dat\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Gender=Neut\|POS=PRON\|PronType=Ind`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Number=Plur\|POS=NOUN`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=ADP`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int`, `Case=Gen\|Number=Plur\|POS=PROPN`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Degree=Cmp\|POS=ADV`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Gen\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADP`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Dat\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Gen\|Number=Sing\|POS=PROPN`, `Case=Nom\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Gen\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `POS=X`, `Case=Dat\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Number=Plur\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Ind`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Dat\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Acc\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Acc\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `POS=SPACE`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Rel`, `POS=DET\|PronType=Ind`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Dat\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Number=Sing\|POS=NOUN`, `Case=Nom\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Degree=Pos\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Acc\|Number=Plur\|POS=NOUN`, `Case=Dat\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|PronType=Rel`, `POS=AUX\|VerbForm=Inf`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Gen\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `POS=ADV\|PronType=Int`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Int`, `POS=AUX\|VerbForm=Part`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Nom\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Dat\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Number=Plur\|POS=DET\|PronType=Ind`, `Degree=Sup\|POS=ADV`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Number=Sing\|POS=NOUN`, `Case=Acc\|Definite=Def\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Dat\|Number=Plur\|POS=DET\|PronType=Ind`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Rel`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Gender=Fem\|POS=NOUN`, `Case=Gen\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Dat\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Nom\|Degree=Cmp\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Dat\|Number=Sing\|POS=PROPN`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Number=Plur\|POS=PROPN`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Rel`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Number=Plur\|POS=DET\|PronType=Rel`, `Case=Dat\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Dat\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Acc\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Rel`, `Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Ind\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Degree=Cmp\|Number=Plur\|POS=ADJ`, `Case=Gen\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Acc\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Ind`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Dem`, `Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Gender=Neut\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PROPN`, `Case=Gen\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Dat\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|POS=PROPN`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Nom\|POS=PROPN`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Acc\|Number=Plur\|POS=PROPN`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Definite=Ind\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Dat\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Gen\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Dat\|Number=Sing\|POS=ADP`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Rel`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=2`, `Case=Nom\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Acc\|Gender=Masc\|POS=NOUN`, `Case=Dat\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Dat\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Acc\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=NOUN`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Gen\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|POS=PROPN`, `Case=Gen\|Definite=Def\|POS=DET\|PronType=Art`, `Case=Gen\|POS=PROPN`, `Case=Acc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=2`, `Case=Dat\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Gen\|POS=PRON\|PronType=Dem`, `Definite=Ind\|POS=DET\|PronType=Art`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Dat\|POS=PRON\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Dat\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Degree=Cmp\|Number=Sing\|POS=ADJ`, `Case=Dat\|Degree=Pos\|Number=Sing\|POS=ADJ`, `POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Number=Sing\|POS=PRON\|PronType=Dem`, `Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Nom\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Nom\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Nom\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Int`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Int`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Nom\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Rel`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Dat\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Gen\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Gen\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Nom\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Number=Sing\|POS=PRON\|PronType=Ind`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Gen\|Number=Plur\|POS=DET\|PronType=Dem`, `Gender=Neut\|POS=DET\|PronType=Ind`, `Case=Dat\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, _(truncated: full list in pipeline meta)_ | | **`parser`** | `ROOT`, `ac`, `adc`, `ag`, `ams`, `app`, `avc`, `cc`, `cd`, `cj`, `cm`, `cp`, `cvc`, `da`, `dep`, `dm`, `ep`, `ju`, `mnr`, `mo`, `ng`, `nk`, `nmc`, `oa`, `oc`, `og`, `op`, `par`, `pd`, `pg`, `ph`, `pm`, `pnc`, `punct`, `rc`, `re`, `rs`, `sb`, `sbp`, `svp`, `uc`, `vo` | | **`ner`** | `LOC`, `MISC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.96 | | `TOKEN_P` | 99.92 | | `TOKEN_R` | 99.90 | | `TOKEN_F` | 99.91 | | `TAG_ACC` | 97.96 | | `POS_ACC` | 98.41 | | `MORPH_ACC` | 92.06 | | `MORPH_MICRO_P` | 96.01 | | `MORPH_MICRO_R` | 95.99 | | `MORPH_MICRO_F` | 96.00 | | `SENTS_P` | 95.18 | | `SENTS_R` | 96.48 | | `SENTS_F` | 95.41 | | `DEP_UAS` | 92.66 | | `DEP_LAS` | 90.78 | | `LEMMA_ACC` | 97.91 | | `ENTS_P` | 85.27 | | `ENTS_R` | 84.44 | | `ENTS_F` | 84.85 |
spacy/de_core_news_sm
spacy
2023-10-10T06:51:41Z
184
1
spacy
[ "spacy", "token-classification", "de", "license:mit", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - de license: mit model-index: - name: de_core_news_sm results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8304823051 - name: NER Recall type: recall value: 0.8106276632 - name: NER F Score type: f_score value: 0.8204348804 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9738469671 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9801441777 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9065560122 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9746015805 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.9192300179 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8984777676 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.937338274 --- ### Details: https://spacy.io/models/de#de_core_news_sm German pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner. | Feature | Description | | --- | --- | | **Name** | `de_core_news_sm` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | | **Sources** | [TIGER Corpus](https://www.ims.uni-stuttgart.de/forschung/ressourcen/korpora/tiger.html) (Brants, Sabine, Stefanie Dipper, Peter Eisenberg, Silvia Hansen, Esther König, Wolfgang Lezius, Christian Rohrer, George Smith, and Hans Uszkoreit)<br />[Tiger2Dep](https://www.ims.uni-stuttgart.de/forschung/ressourcen/werkzeuge/tiger2dep/) (Wolfgang Seeker)<br />[WikiNER](https://figshare.com/articles/Learning_multilingual_named_entity_recognition_from_Wikipedia/5462500) (Joel Nothman, Nicky Ringland, Will Radford, Tara Murphy, James R Curran) | | **License** | `MIT` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (772 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `$(`, `$,`, `$.`, `ADJA`, `ADJD`, `ADV`, `APPO`, `APPR`, `APPRART`, `APZR`, `ART`, `CARD`, `FM`, `ITJ`, `KOKOM`, `KON`, `KOUI`, `KOUS`, `NE`, `NN`, `NNE`, `PDAT`, `PDS`, `PIAT`, `PIS`, `PPER`, `PPOSAT`, `PPOSS`, `PRELAT`, `PRELS`, `PRF`, `PROAV`, `PTKA`, `PTKANT`, `PTKNEG`, `PTKVZ`, `PTKZU`, `PWAT`, `PWAV`, `PWS`, `TRUNC`, `VAFIN`, `VAIMP`, `VAINF`, `VAPP`, `VMFIN`, `VMINF`, `VMPP`, `VVFIN`, `VVIMP`, `VVINF`, `VVIZU`, `VVPP`, `XY`, `_SP` | | **`morphologizer`** | `POS=PUNCT`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `POS=ADV`, `Case=Nom\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=ADP`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PROPN`, `POS=VERB\|VerbForm=Part`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Foreign=Yes\|POS=X`, `Degree=Pos\|POS=ADV`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=ADP`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Dat\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Dat\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Dat\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=CCONJ`, `POS=SCONJ`, `Case=Acc\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `POS=VERB\|VerbForm=Inf`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Acc\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=NOUN`, `POS=PART`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Dat\|Definite=Def\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Dat\|Number=Plur\|POS=PROPN`, `POS=PRON\|PronType=Ind`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Dat\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Sing\|POS=PROPN`, `Case=Dat\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=NOUN`, `POS=NUM`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=ADP`, `Gender=Neut\|POS=NOUN`, `Case=Acc\|Number=Sing\|POS=PROPN`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Gen\|Definite=Def\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Definite=Def\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `POS=PROPN`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `POS=INTJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Rel`, `Gender=Masc\|POS=NOUN`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `POS=SCONJ\|PronType=Int`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Dat\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Dat\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Gender=Neut\|POS=PRON\|PronType=Ind`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Number=Plur\|POS=NOUN`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=ADP`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int`, `Case=Gen\|Number=Plur\|POS=PROPN`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Degree=Cmp\|POS=ADV`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Gen\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADP`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Dat\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Gen\|Number=Sing\|POS=PROPN`, `Case=Nom\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Gen\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `POS=X`, `Case=Dat\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Number=Plur\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Ind`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Dat\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Acc\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Acc\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `POS=SPACE`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Rel`, `POS=DET\|PronType=Ind`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Dat\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Number=Sing\|POS=NOUN`, `Case=Nom\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Degree=Pos\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Acc\|Number=Plur\|POS=NOUN`, `Case=Dat\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|PronType=Rel`, `POS=AUX\|VerbForm=Inf`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Gen\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `POS=ADV\|PronType=Int`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Int`, `POS=AUX\|VerbForm=Part`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Nom\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Dat\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Number=Plur\|POS=DET\|PronType=Ind`, `Degree=Sup\|POS=ADV`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Number=Sing\|POS=NOUN`, `Case=Acc\|Definite=Def\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Dat\|Number=Plur\|POS=DET\|PronType=Ind`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Rel`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Gender=Fem\|POS=NOUN`, `Case=Gen\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Dat\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Nom\|Degree=Cmp\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Dat\|Number=Sing\|POS=PROPN`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Number=Plur\|POS=PROPN`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Rel`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Number=Plur\|POS=DET\|PronType=Rel`, `Case=Dat\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Dat\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Acc\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Rel`, `Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Ind\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Degree=Cmp\|Number=Plur\|POS=ADJ`, `Case=Gen\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Acc\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Ind`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Dem`, `Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Gender=Neut\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PROPN`, `Case=Gen\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Dat\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|POS=PROPN`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Nom\|POS=PROPN`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Acc\|Number=Plur\|POS=PROPN`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Definite=Ind\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Dat\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Gen\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Dat\|Number=Sing\|POS=ADP`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Rel`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=2`, `Case=Nom\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Acc\|Gender=Masc\|POS=NOUN`, `Case=Dat\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Dat\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Acc\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=NOUN`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Gen\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|POS=PROPN`, `Case=Gen\|Definite=Def\|POS=DET\|PronType=Art`, `Case=Gen\|POS=PROPN`, `Case=Acc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=2`, `Case=Dat\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Gen\|POS=PRON\|PronType=Dem`, `Definite=Ind\|POS=DET\|PronType=Art`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Dat\|POS=PRON\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Dat\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Degree=Cmp\|Number=Sing\|POS=ADJ`, `Case=Dat\|Degree=Pos\|Number=Sing\|POS=ADJ`, `POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Number=Sing\|POS=PRON\|PronType=Dem`, `Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Nom\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Nom\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Nom\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Int`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Int`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Nom\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Rel`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Dat\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Gen\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Gen\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Nom\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Number=Sing\|POS=PRON\|PronType=Ind`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Gen\|Number=Plur\|POS=DET\|PronType=Dem`, `Gender=Neut\|POS=DET\|PronType=Ind`, `Case=Dat\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, _(truncated: full list in pipeline meta)_ | | **`parser`** | `ROOT`, `ac`, `adc`, `ag`, `ams`, `app`, `avc`, `cc`, `cd`, `cj`, `cm`, `cp`, `cvc`, `da`, `dep`, `dm`, `ep`, `ju`, `mnr`, `mo`, `ng`, `nk`, `nmc`, `oa`, `oc`, `og`, `op`, `par`, `pd`, `pg`, `ph`, `pm`, `pnc`, `punct`, `rc`, `re`, `rs`, `sb`, `sbp`, `svp`, `uc`, `vo` | | **`ner`** | `LOC`, `MISC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.96 | | `TOKEN_P` | 99.92 | | `TOKEN_R` | 99.90 | | `TOKEN_F` | 99.91 | | `TAG_ACC` | 97.38 | | `POS_ACC` | 98.01 | | `MORPH_ACC` | 90.66 | | `MORPH_MICRO_P` | 95.03 | | `MORPH_MICRO_R` | 95.15 | | `MORPH_MICRO_F` | 95.09 | | `SENTS_P` | 94.27 | | `SENTS_R` | 95.28 | | `SENTS_F` | 93.73 | | `DEP_UAS` | 91.92 | | `DEP_LAS` | 89.85 | | `LEMMA_ACC` | 97.46 | | `ENTS_P` | 83.05 | | `ENTS_R` | 81.06 | | `ENTS_F` | 82.04 |
spacy/el_core_news_lg
spacy
2023-10-10T06:51:38Z
13
0
spacy
[ "spacy", "token-classification", "el", "license:cc-by-nc-sa-3.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - el license: cc-by-nc-sa-3.0 model-index: - name: el_core_news_lg results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7540322581 - name: NER Recall type: recall value: 0.7857142857 - name: NER F Score type: f_score value: 0.7695473251 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9329980772 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.962973919 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9114036385 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.8956268797 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8824531516 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8454140792 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9259259259 --- ### Details: https://spacy.io/models/el#el_core_news_lg Greek pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner, attribute_ruler. | Feature | Description | | --- | --- | | **Name** | `el_core_news_lg` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) | | **Sources** | [UD Greek GDT v2.8](https://github.com/UniversalDependencies/UD_Greek-GDT) (Prokopidis, Prokopis)<br />[Greek NER Corpus (Google Summer of Code 2018)](https://github.com/eellak/gsoc2018-spacy) (Giannis Daras)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `CC BY-NC-SA 3.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (395 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `Case=Nom\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Foreign=Yes\|POS=X`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `POS=ADP`, `Case=Acc\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `NumType=Card\|POS=NUM`, `POS=NOUN`, `POS=ADV`, `POS=PUNCT`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=ADP`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADP`, `Case=Acc\|Gender=Neut\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=CCONJ`, `Case=Nom\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `POS=AUX`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=ADP`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADP`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Acc\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=ADP`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|POS=VERB\|VerbForm=Conv\|Voice=Act`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=ADP`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=SCONJ`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|POS=VERB\|VerbForm=Inf\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Aspect=Perf\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PROPN`, `POS=PART`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Gender=Fem\|NumType=Ord\|Number=Sing\|POS=NUM`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Abbr=Yes\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Voc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Degree=Cmp\|POS=ADV`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Acc\|Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Gen\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Gen\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Voc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Voc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Voc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Acc\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `POS=SPACE`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Aspect=Perf\|Case=Acc\|Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Abbr=Yes\|POS=ADV`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Nom\|Gender=Neut\|NumType=Ord\|Number=Plur\|POS=NUM`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Perf\|Case=Nom\|Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Acc\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Gen\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Fem\|NumType=Sets\|Number=Plur\|POS=NUM`, `Aspect=Imp\|POS=AUX\|VerbForm=Conv\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Gender=Fem\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Nom\|Gender=Fem\|NumType=Sets\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Perf\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Voc\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Voc\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Masc\|NumType=Ord\|Number=Sing\|POS=NUM`, `Aspect=Perf\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Neut\|NumType=Ord\|Number=Sing\|POS=NUM`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Gen\|Gender=Fem\|NumType=Sets\|Number=Plur\|POS=NUM`, `Aspect=Perf\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Neut\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Nom\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Nom\|Gender=Fem\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Gen\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Nom\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Aspect=Perf\|Case=Gen\|Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Fem\|NumType=Mult\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|NumType=Mult\|Number=Sing\|POS=NUM`, `Case=Nom\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Int`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Degree=Sup\|POS=ADV`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Int`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `POS=SYM`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Nom\|Gender=Masc\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Aspect=Perf\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Case=Nom\|Gender=Neut\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|NumType=Mult\|Number=Sing\|POS=NUM`, `Case=Acc\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Case=Gen\|Gender=Neut\|NumType=Ord\|Number=Sing\|POS=NUM`, `Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Gen\|Gender=Fem\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Dat\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ` | | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `case`, `cc`, `ccomp`, `conj`, `cop`, `csubj`, `csubj:pass`, `dep`, `det`, `fixed`, `flat`, `iobj`, `mark`, `nmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `obl:agent`, `parataxis`, `punct`, `vocative`, `xcomp` | | **`ner`** | `EVENT`, `GPE`, `LOC`, `ORG`, `PERSON`, `PRODUCT` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 100.00 | | `TOKEN_P` | 99.90 | | `TOKEN_R` | 99.95 | | `TOKEN_F` | 99.93 | | `POS_ACC` | 96.30 | | `MORPH_ACC` | 91.14 | | `MORPH_MICRO_P` | 96.20 | | `MORPH_MICRO_R` | 95.96 | | `MORPH_MICRO_F` | 96.08 | | `SENTS_P` | 92.14 | | `SENTS_R` | 93.05 | | `SENTS_F` | 92.59 | | `DEP_UAS` | 88.25 | | `DEP_LAS` | 84.54 | | `LEMMA_ACC` | 89.56 | | `TAG_ACC` | 93.30 | | `ENTS_P` | 75.40 | | `ENTS_R` | 78.57 | | `ENTS_F` | 76.95 |
spacy/el_core_news_md
spacy
2023-10-10T06:50:50Z
7
0
spacy
[ "spacy", "token-classification", "el", "license:cc-by-nc-sa-3.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - el license: cc-by-nc-sa-3.0 model-index: - name: el_core_news_md results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7594936709 - name: NER Recall type: recall value: 0.756302521 - name: NER F Score type: f_score value: 0.7578947368 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9324064488 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9623822906 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9064734014 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.8884287334 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8759067927 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.836887228 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9511889862 --- ### Details: https://spacy.io/models/el#el_core_news_md Greek pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner, attribute_ruler. | Feature | Description | | --- | --- | | **Name** | `el_core_news_md` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 500000 keys, 20000 unique vectors (300 dimensions) | | **Sources** | [UD Greek GDT v2.8](https://github.com/UniversalDependencies/UD_Greek-GDT) (Prokopidis, Prokopis)<br />[Greek NER Corpus (Google Summer of Code 2018)](https://github.com/eellak/gsoc2018-spacy) (Giannis Daras)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `CC BY-NC-SA 3.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (395 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `Case=Nom\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Foreign=Yes\|POS=X`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `POS=ADP`, `Case=Acc\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `NumType=Card\|POS=NUM`, `POS=NOUN`, `POS=ADV`, `POS=PUNCT`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=ADP`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADP`, `Case=Acc\|Gender=Neut\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=CCONJ`, `Case=Nom\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `POS=AUX`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=ADP`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADP`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Acc\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=ADP`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|POS=VERB\|VerbForm=Conv\|Voice=Act`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=ADP`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=SCONJ`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|POS=VERB\|VerbForm=Inf\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Aspect=Perf\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PROPN`, `POS=PART`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Gender=Fem\|NumType=Ord\|Number=Sing\|POS=NUM`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Abbr=Yes\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Voc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Degree=Cmp\|POS=ADV`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Acc\|Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Gen\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Gen\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Voc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Voc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Voc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Acc\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `POS=SPACE`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Aspect=Perf\|Case=Acc\|Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Abbr=Yes\|POS=ADV`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Nom\|Gender=Neut\|NumType=Ord\|Number=Plur\|POS=NUM`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Perf\|Case=Nom\|Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Acc\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Gen\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Fem\|NumType=Sets\|Number=Plur\|POS=NUM`, `Aspect=Imp\|POS=AUX\|VerbForm=Conv\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Gender=Fem\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Nom\|Gender=Fem\|NumType=Sets\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Perf\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Voc\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Voc\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Masc\|NumType=Ord\|Number=Sing\|POS=NUM`, `Aspect=Perf\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Neut\|NumType=Ord\|Number=Sing\|POS=NUM`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Gen\|Gender=Fem\|NumType=Sets\|Number=Plur\|POS=NUM`, `Aspect=Perf\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Neut\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Nom\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Nom\|Gender=Fem\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Gen\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Nom\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Aspect=Perf\|Case=Gen\|Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Fem\|NumType=Mult\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|NumType=Mult\|Number=Sing\|POS=NUM`, `Case=Nom\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Int`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Degree=Sup\|POS=ADV`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Int`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `POS=SYM`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Nom\|Gender=Masc\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Aspect=Perf\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Case=Nom\|Gender=Neut\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|NumType=Mult\|Number=Sing\|POS=NUM`, `Case=Acc\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Case=Gen\|Gender=Neut\|NumType=Ord\|Number=Sing\|POS=NUM`, `Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Gen\|Gender=Fem\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Dat\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ` | | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `case`, `cc`, `ccomp`, `conj`, `cop`, `csubj`, `csubj:pass`, `dep`, `det`, `fixed`, `flat`, `iobj`, `mark`, `nmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `obl:agent`, `parataxis`, `punct`, `vocative`, `xcomp` | | **`ner`** | `EVENT`, `GPE`, `LOC`, `ORG`, `PERSON`, `PRODUCT` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 100.00 | | `TOKEN_P` | 99.90 | | `TOKEN_R` | 99.95 | | `TOKEN_F` | 99.93 | | `POS_ACC` | 96.24 | | `MORPH_ACC` | 90.65 | | `MORPH_MICRO_P` | 96.02 | | `MORPH_MICRO_R` | 95.85 | | `MORPH_MICRO_F` | 95.93 | | `SENTS_P` | 95.96 | | `SENTS_R` | 94.29 | | `SENTS_F` | 95.12 | | `DEP_UAS` | 87.59 | | `DEP_LAS` | 83.69 | | `LEMMA_ACC` | 88.84 | | `TAG_ACC` | 93.24 | | `ENTS_P` | 75.95 | | `ENTS_R` | 75.63 | | `ENTS_F` | 75.79 |
spacy/el_core_news_sm
spacy
2023-10-10T06:50:44Z
5
1
spacy
[ "spacy", "token-classification", "el", "license:cc-by-nc-sa-3.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - el license: cc-by-nc-sa-3.0 model-index: - name: el_core_news_sm results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.742081448 - name: NER Recall type: recall value: 0.6890756303 - name: NER F Score type: f_score value: 0.7145969499 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9127841049 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9427599468 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.8905980378 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.8865552433 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8463356974 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8032327231 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9372693727 --- ### Details: https://spacy.io/models/el#el_core_news_sm Greek pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner, attribute_ruler. | Feature | Description | | --- | --- | | **Name** | `el_core_news_sm` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | | **Sources** | [UD Greek GDT v2.8](https://github.com/UniversalDependencies/UD_Greek-GDT) (Prokopidis, Prokopis)<br />[Greek NER Corpus (Google Summer of Code 2018)](https://github.com/eellak/gsoc2018-spacy) (Giannis Daras) | | **License** | `CC BY-NC-SA 3.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (395 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `Case=Nom\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Foreign=Yes\|POS=X`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `POS=ADP`, `Case=Acc\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `NumType=Card\|POS=NUM`, `POS=NOUN`, `POS=ADV`, `POS=PUNCT`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=ADP`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADP`, `Case=Acc\|Gender=Neut\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=CCONJ`, `Case=Nom\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `POS=AUX`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=ADP`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADP`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Acc\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=ADP`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|POS=VERB\|VerbForm=Conv\|Voice=Act`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=ADP`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=SCONJ`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|POS=VERB\|VerbForm=Inf\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Aspect=Perf\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PROPN`, `POS=PART`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Gender=Fem\|NumType=Ord\|Number=Sing\|POS=NUM`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Abbr=Yes\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Voc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Degree=Cmp\|POS=ADV`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Acc\|Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Gen\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Gen\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Voc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Voc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Voc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Acc\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `POS=SPACE`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Aspect=Perf\|Case=Acc\|Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Abbr=Yes\|POS=ADV`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Nom\|Gender=Neut\|NumType=Ord\|Number=Plur\|POS=NUM`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Aspect=Perf\|Case=Nom\|Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Acc\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Gen\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Fem\|NumType=Sets\|Number=Plur\|POS=NUM`, `Aspect=Imp\|POS=AUX\|VerbForm=Conv\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Gender=Fem\|NumType=Ord\|Number=Sing\|POS=NUM`, `Case=Nom\|Gender=Fem\|NumType=Sets\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Perf\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Voc\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Voc\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Masc\|NumType=Ord\|Number=Sing\|POS=NUM`, `Aspect=Perf\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Neut\|NumType=Ord\|Number=Sing\|POS=NUM`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Gen\|Gender=Fem\|NumType=Sets\|Number=Plur\|POS=NUM`, `Aspect=Perf\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Neut\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Nom\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Gen\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Nom\|Gender=Fem\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Gen\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Nom\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Aspect=Perf\|Case=Gen\|Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Fem\|NumType=Mult\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|NumType=Mult\|Number=Sing\|POS=NUM`, `Case=Nom\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Int`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind`, `Degree=Sup\|POS=ADV`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Int`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `POS=SYM`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Rel`, `Case=Nom\|Gender=Masc\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Aspect=Perf\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Rel`, `Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Case=Nom\|Gender=Neut\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|NumType=Mult\|Number=Sing\|POS=NUM`, `Case=Acc\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Case=Gen\|Gender=Neut\|NumType=Ord\|Number=Sing\|POS=NUM`, `Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind`, `Case=Gen\|Gender=Fem\|NumType=Ord\|Number=Plur\|POS=NUM`, `Case=Dat\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ` | | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `case`, `cc`, `ccomp`, `conj`, `cop`, `csubj`, `csubj:pass`, `dep`, `det`, `fixed`, `flat`, `iobj`, `mark`, `nmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `obl:agent`, `parataxis`, `punct`, `vocative`, `xcomp` | | **`ner`** | `EVENT`, `GPE`, `LOC`, `ORG`, `PERSON`, `PRODUCT` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 100.00 | | `TOKEN_P` | 99.90 | | `TOKEN_R` | 99.95 | | `TOKEN_F` | 99.93 | | `POS_ACC` | 94.28 | | `MORPH_ACC` | 89.06 | | `MORPH_MICRO_P` | 94.85 | | `MORPH_MICRO_R` | 94.52 | | `MORPH_MICRO_F` | 94.69 | | `SENTS_P` | 92.93 | | `SENTS_R` | 94.54 | | `SENTS_F` | 93.73 | | `DEP_UAS` | 84.63 | | `DEP_LAS` | 80.32 | | `LEMMA_ACC` | 88.66 | | `TAG_ACC` | 91.28 | | `ENTS_P` | 74.21 | | `ENTS_R` | 68.91 | | `ENTS_F` | 71.46 |
spacy/es_core_news_md
spacy
2023-10-10T06:49:00Z
311
1
spacy
[ "spacy", "token-classification", "es", "license:gpl-3.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - es license: gpl-3.0 model-index: - name: es_core_news_md results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8925237438 - name: NER Recall type: recall value: 0.8951031872 - name: NER F Score type: f_score value: 0.8938116045 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9610850187 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9848174063 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9802342746 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.964971968 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.9125758682 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8800383563 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9880453102 --- ### Details: https://spacy.io/models/es#es_core_news_md Spanish pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer. | Feature | Description | | --- | --- | | **Name** | `es_core_news_md` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` | | **Vectors** | 500000 keys, 20000 unique vectors (300 dimensions) | | **Sources** | [UD Spanish AnCora v2.8](https://github.com/UniversalDependencies/UD_Spanish-AnCora) (Martínez Alonso, Héctor; Zeman, Daniel)<br />[WikiNER](https://figshare.com/articles/Learning_multilingual_named_entity_recognition_from_Wikipedia/5462500) (Joel Nothman, Nicky Ringland, Will Radford, Tara Murphy, James R Curran)<br />[spaCy lookups data](https://github.com/explosion/spacy-lookups-data) (Explosion)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `GNU GPL 3.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (468 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=NOUN`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=ADP\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=ADJ`, `POS=ADP`, `Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `POS=PROPN`, `Case=Acc\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `POS=VERB\|VerbForm=Inf`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Fem\|Number=Sing\|POS=NOUN`, `Gender=Fem\|Number=Plur\|POS=NOUN`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `POS=PRON\|PronType=Int,Rel`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `POS=SCONJ`, `POS=NOUN`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Number=Plur\|POS=NOUN`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Gender=Masc\|Number=Plur\|POS=NOUN`, `POS=PUNCT\|PunctType=Peri`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `POS=PUNCT\|PunctType=Comm`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Number=Plur\|POS=ADJ`, `POS=CCONJ`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Ind`, `POS=ADV`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Dem`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Number=Sing\|POS=ADJ`, `Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Tot`, `POS=PRON\|PronType=Ind`, `POS=ADV\|Polarity=Neg`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `Gender=Fem\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|PronType=Int,Rel`, `POS=PUNCT\|PunctType=Quot`, `POS=PUNCT`, `Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `POS=PUNCT\|PunctSide=Ini\|PunctType=Brck`, `POS=PUNCT\|PunctSide=Fin\|PunctType=Brck`, `NumForm=Digit\|NumType=Card\|POS=NUM`, `NumType=Card\|POS=NUM`, `POS=VERB\|VerbForm=Ger`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Fem\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Number=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Number=Sing\|POS=NOUN`, `Gender=Masc\|Number=Plur\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Degree=Cmp\|POS=ADV`, `POS=AUX\|VerbForm=Inf`, `Number=Plur\|POS=DET\|PronType=Ind`, `Number=Plur\|POS=DET\|PronType=Dem`, `POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Degree=Cmp\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Case=Acc\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `AdvType=Tim\|POS=NOUN`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Ind`, `NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `NumForm=Digit\|POS=NOUN`, `Number=Sing\|POS=PRON\|PronType=Dem`, `Number=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Gender=Fem\|Number=Plur\|POS=ADJ`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Ind`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Gender=Masc\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Gender=Masc\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part`, `Number=Sing\|POS=DET\|PronType=Tot`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Dat\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Degree=Cmp\|Number=Plur\|POS=ADJ`, `POS=AUX\|VerbForm=Ger`, `Gender=Fem\|POS=NOUN`, `Gender=Fem\|NumType=Ord\|Number=Sing\|POS=ADJ`, `AdvType=Tim\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Int,Rel`, `Number=Sing\|POS=PRON\|PronType=Int,Rel`, `POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Acc,Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Definite=Ind\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Acc,Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `POS=SPACE`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Number=Plur\|POS=PRON\|PronType=Ind`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `POS=PART`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Number=Sing\|POS=DET\|PronType=Ind`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=3\|VerbForm=Fin`, `NumForm=Digit\|POS=SYM`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Dem`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=1\|VerbForm=Fin`, `NumForm=Digit\|NumType=Frac\|POS=NUM`, `Gender=Fem\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Int,Rel`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs`, `Definite=Ind\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `POS=PUNCT\|PunctType=Colo`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Neg`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `Gender=Fem\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Number=Sing\|POS=PRON\|PronType=Neg`, `POS=PUNCT\|PunctType=Semi`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Sing\|POS=PRON\|PronType=Ind`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Case=Acc,Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `POS=INTJ`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=PRON\|PronType=Dem`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `POS=PUNCT\|PunctType=Dash`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Neg`, `Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Tot`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `Gender=Masc\|POS=NOUN`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Ind`, `Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Acc\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Ger`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `POS=NOUN\|VerbForm=Inf`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Int,Rel`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Dem`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Neg`, `Case=Acc\|Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Degree=Abs\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Acc,Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Imp\|Number=Sing\|POS=AUX\|Person=3\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `POS=DET\|PronType=Ind`, `POS=DET\|PronType=Int,Rel`, `AdvType=Tim\|POS=ADV`, `POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=3\|VerbForm=Fin`, `Case=Dat\|Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `POS=PUNCT\|PunctSide=Ini\|PunctType=Qest`, `POS=PUNCT\|PunctSide=Fin\|PunctType=Qest`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs`, `Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Ind`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Degree=Abs\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `POS=PUNCT\|PunctSide=Ini\|PunctType=Excl`, `POS=PUNCT\|PunctSide=Fin\|PunctType=Excl`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin`, `Case=Acc\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Tot`, `Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=PRON\|PronType=Ind`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=PRON\|PronType=Ind`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Dat\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Degree=Abs\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Pre\|PronType=Prs`, `Case=Dat\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Fin`, `Definite=Ind\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `POS=SCONJ\|PronType=Int,Rel`, `Case=Acc,Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Reflex=Yes`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `NumType=Card\|Number=Sing\|POS=DET\|PronType=Ind`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs`, `Case=Dat\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Ger`, `Case=Acc,Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc,Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `POS=SYM`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Neg`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Ger`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=2,3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Ind`, `Case=Acc,Nom\|Number=Sing\|POS=PRON\|Person=2\|Polite=Form\|PronType=Prs`, `Case=Dat\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=PRON\|PronType=Int,Rel`, `Gender=Fem\|NumType=Card\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Dat\|Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Case=Acc,Dat\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=2\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=1\|VerbForm=Fin`, `NumType=Card\|Number=Plur\|POS=PRON\|PronType=Ind`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Dem`, `Degree=Abs\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Gender=Fem\|Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Int,Rel`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Acc,Nom\|Number=Plur\|POS=PRON\|Person=2\|Polite=Form\|PronType=Prs`, `Mood=Imp\|Number=Sing\|POS=AUX\|Person=2\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person=2\|Poss=Yes\|PronType=Ind`, `NumType=Card\|Number=Sing\|POS=NUM`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Com\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Pre\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Imp\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Number=Sing\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Pre\|PronType=Prs`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=2\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Number=Sing\|POS=NOUN\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Case=Dat\|Mood=Imp\|Number=Plur,Sing\|POS=VERB\|Person=1,2\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Case=Acc\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Fut\|VerbForm=Fin`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Fut\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Tot`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Number=Sing\|POS=VERB\|VerbForm=Fin`, `POS=VERB\|VerbForm=Fin`, `Degree=Abs\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Degree=Abs\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Ger`, `Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Dem`, `Definite=Ind\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Art`, `Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Acc,Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Gender=Masc\|Number=Sing\|POS=AUX\|VerbForm=Fin`, `POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Gender=Masc\|Number=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=PRON\|PronType=Int,Rel`, `Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Acc,Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Acc,Dat\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Ind`, `Mood=Ind\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Definite=Def\|Foreign=Yes\|POS=DET\|PronType=Art`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=PRON\|PronType=Dem`, `Gender=Fem\|Number=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=ADP\|PronType=Art`, `Case=Acc\|Number=Sing\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|PunctType=Quot\|VerbForm=Inf`, `Case=Dat\|Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Com\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Reflex=Yes`, `NumForm=Digit\|NumType=Frac\|POS=SYM`, `Number=Sing\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Dat\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Case=Dat\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Acc,Dat\|Gender=Masc\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Case=Acc,Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Ind`, `Case=Dat\|Number=Plur\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Acc\|Number=Plur\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Number=Sing\|POS=PRON\|PronType=Tot`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `POS=PRON\|PronType=Dem`, `Number=Sing\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `POS=AUX\|VerbForm=Fin`, `Gender=Fem\|NumType=Card\|Number=Plur\|POS=PRON\|PronType=Int,Rel`, `Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Case=Acc,Dat\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `AdvType=Tim\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|Typo=Yes\|VerbForm=Fin`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Acc\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Ind`, `Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person=2\|Poss=Yes\|PronType=Ind`, `Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=ADP\|PronType=Art`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=NOUN\|VerbForm=Part`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Case=Acc,Dat\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Gender=Masc\|Number=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Ind`, `Case=Acc\|Number=Sing\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Ger`, `Case=Acc,Dat\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Gender=Fem\|Number=Sing\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Com\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Pre\|PronType=Prs`, `POS=X`, `Case=Acc,Dat\|Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs`, `Case=Com\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Case=Acc,Dat\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Acc,Dat\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Mood=Imp\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs`, `Number=Sing\|POS=AUX\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Acc\|Gender=Masc\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|Poss=Yes\|PronType=Ind`, `Case=Dat\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `POS=NOUN\|PunctType=Comm`, `Degree=Cmp\|POS=ADJ`, `Gender=Masc\|POS=ADJ`, `Degree=Abs\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=PRON\|PronType=Ind`, `POS=PRON\|PronType=Neg`, `Case=Acc,Dat\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Ger`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Gender=Fem\|Number=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Ind`, `Number=Sing\|POS=DET\|PronType=Int,Rel`, `Definite=Def\|Foreign=Yes\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Foreign=Yes\|POS=NOUN`, `Foreign=Yes\|POS=ADP`, `Foreign=Yes\|POS=CCONJ`, `Foreign=Yes\|POS=PROPN` | | **`parser`** | `ROOT`, `acl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `case`, `cc`, `ccomp`, `compound`, `conj`, `cop`, `csubj`, `dep`, `det`, `expl:impers`, `expl:pass`, `expl:pv`, `fixed`, `flat`, `iobj`, `mark`, `nmod`, `nsubj`, `nummod`, `obj`, `obl`, `parataxis`, `punct`, `xcomp` | | **`ner`** | `LOC`, `MISC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 100.00 | | `TOKEN_P` | 99.89 | | `TOKEN_R` | 99.95 | | `TOKEN_F` | 99.92 | | `POS_ACC` | 98.48 | | `MORPH_ACC` | 98.02 | | `MORPH_MICRO_P` | 99.43 | | `MORPH_MICRO_R` | 98.85 | | `MORPH_MICRO_F` | 99.14 | | `SENTS_P` | 98.40 | | `SENTS_R` | 99.21 | | `SENTS_F` | 98.80 | | `DEP_UAS` | 91.26 | | `DEP_LAS` | 88.00 | | `TAG_ACC` | 96.11 | | `LEMMA_ACC` | 96.50 | | `ENTS_P` | 89.25 | | `ENTS_R` | 89.51 | | `ENTS_F` | 89.38 |
spacy/es_core_news_sm
spacy
2023-10-10T06:48:54Z
159
2
spacy
[ "spacy", "token-classification", "es", "license:gpl-3.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - es license: gpl-3.0 model-index: - name: es_core_news_sm results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8910285087 - name: NER Recall type: recall value: 0.8918264338 - name: NER F Score type: f_score value: 0.8914272927 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9581496108 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9815191135 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9771762157 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9629594135 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.9037516481 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8684594765 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.972165913 --- ### Details: https://spacy.io/models/es#es_core_news_sm Spanish pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer. | Feature | Description | | --- | --- | | **Name** | `es_core_news_sm` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` | | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | | **Sources** | [UD Spanish AnCora v2.8](https://github.com/UniversalDependencies/UD_Spanish-AnCora) (Martínez Alonso, Héctor; Zeman, Daniel)<br />[WikiNER](https://figshare.com/articles/Learning_multilingual_named_entity_recognition_from_Wikipedia/5462500) (Joel Nothman, Nicky Ringland, Will Radford, Tara Murphy, James R Curran)<br />[spaCy lookups data](https://github.com/explosion/spacy-lookups-data) (Explosion) | | **License** | `GNU GPL 3.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (468 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=NOUN`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=ADP\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=ADJ`, `POS=ADP`, `Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `POS=PROPN`, `Case=Acc\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `POS=VERB\|VerbForm=Inf`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Fem\|Number=Sing\|POS=NOUN`, `Gender=Fem\|Number=Plur\|POS=NOUN`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `POS=PRON\|PronType=Int,Rel`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `POS=SCONJ`, `POS=NOUN`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Number=Plur\|POS=NOUN`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Gender=Masc\|Number=Plur\|POS=NOUN`, `POS=PUNCT\|PunctType=Peri`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `POS=PUNCT\|PunctType=Comm`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Number=Plur\|POS=ADJ`, `POS=CCONJ`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Ind`, `POS=ADV`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Dem`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Number=Sing\|POS=ADJ`, `Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Tot`, `POS=PRON\|PronType=Ind`, `POS=ADV\|Polarity=Neg`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `Gender=Fem\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|PronType=Int,Rel`, `POS=PUNCT\|PunctType=Quot`, `POS=PUNCT`, `Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `POS=PUNCT\|PunctSide=Ini\|PunctType=Brck`, `POS=PUNCT\|PunctSide=Fin\|PunctType=Brck`, `NumForm=Digit\|NumType=Card\|POS=NUM`, `NumType=Card\|POS=NUM`, `POS=VERB\|VerbForm=Ger`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Fem\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Number=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Number=Sing\|POS=NOUN`, `Gender=Masc\|Number=Plur\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Degree=Cmp\|POS=ADV`, `POS=AUX\|VerbForm=Inf`, `Number=Plur\|POS=DET\|PronType=Ind`, `Number=Plur\|POS=DET\|PronType=Dem`, `POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Degree=Cmp\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Case=Acc\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `AdvType=Tim\|POS=NOUN`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Ind`, `NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `NumForm=Digit\|POS=NOUN`, `Number=Sing\|POS=PRON\|PronType=Dem`, `Number=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Gender=Fem\|Number=Plur\|POS=ADJ`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Ind`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Gender=Masc\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Gender=Masc\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part`, `Number=Sing\|POS=DET\|PronType=Tot`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Dat\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Degree=Cmp\|Number=Plur\|POS=ADJ`, `POS=AUX\|VerbForm=Ger`, `Gender=Fem\|POS=NOUN`, `Gender=Fem\|NumType=Ord\|Number=Sing\|POS=ADJ`, `AdvType=Tim\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Int,Rel`, `Number=Sing\|POS=PRON\|PronType=Int,Rel`, `POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Acc,Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Definite=Ind\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Acc,Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `POS=SPACE`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Number=Plur\|POS=PRON\|PronType=Ind`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `POS=PART`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Number=Sing\|POS=DET\|PronType=Ind`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=3\|VerbForm=Fin`, `NumForm=Digit\|POS=SYM`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Dem`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=1\|VerbForm=Fin`, `NumForm=Digit\|NumType=Frac\|POS=NUM`, `Gender=Fem\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Int,Rel`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs`, `Definite=Ind\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `POS=PUNCT\|PunctType=Colo`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Neg`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `Gender=Fem\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Number=Sing\|POS=PRON\|PronType=Neg`, `POS=PUNCT\|PunctType=Semi`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Sing\|POS=PRON\|PronType=Ind`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Case=Acc,Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `POS=INTJ`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=PRON\|PronType=Dem`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `POS=PUNCT\|PunctType=Dash`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Neg`, `Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Tot`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `Gender=Masc\|POS=NOUN`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Ind`, `Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Acc\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Ger`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `POS=NOUN\|VerbForm=Inf`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Int,Rel`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Dem`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Neg`, `Case=Acc\|Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Degree=Abs\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Acc,Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Imp\|Number=Sing\|POS=AUX\|Person=3\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `POS=DET\|PronType=Ind`, `POS=DET\|PronType=Int,Rel`, `AdvType=Tim\|POS=ADV`, `POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=3\|VerbForm=Fin`, `Case=Dat\|Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `POS=PUNCT\|PunctSide=Ini\|PunctType=Qest`, `POS=PUNCT\|PunctSide=Fin\|PunctType=Qest`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs`, `Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Ind`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Degree=Abs\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `POS=PUNCT\|PunctSide=Ini\|PunctType=Excl`, `POS=PUNCT\|PunctSide=Fin\|PunctType=Excl`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin`, `Case=Acc\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Tot`, `Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=PRON\|PronType=Ind`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=PRON\|PronType=Ind`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Dat\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Degree=Abs\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Pre\|PronType=Prs`, `Case=Dat\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Fin`, `Definite=Ind\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `POS=SCONJ\|PronType=Int,Rel`, `Case=Acc,Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Reflex=Yes`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `NumType=Card\|Number=Sing\|POS=DET\|PronType=Ind`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs`, `Case=Dat\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Ger`, `Case=Acc,Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc,Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `POS=SYM`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Neg`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Ger`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=2,3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Ind`, `Case=Acc,Nom\|Number=Sing\|POS=PRON\|Person=2\|Polite=Form\|PronType=Prs`, `Case=Dat\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=PRON\|PronType=Int,Rel`, `Gender=Fem\|NumType=Card\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Dat\|Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Case=Acc,Dat\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=2\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=1\|VerbForm=Fin`, `NumType=Card\|Number=Plur\|POS=PRON\|PronType=Ind`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Dem`, `Degree=Abs\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Gender=Fem\|Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Int,Rel`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Acc,Nom\|Number=Plur\|POS=PRON\|Person=2\|Polite=Form\|PronType=Prs`, `Mood=Imp\|Number=Sing\|POS=AUX\|Person=2\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person=2\|Poss=Yes\|PronType=Ind`, `NumType=Card\|Number=Sing\|POS=NUM`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Com\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Pre\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Imp\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Number=Sing\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Pre\|PronType=Prs`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=2\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Number=Sing\|POS=NOUN\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Case=Dat\|Mood=Imp\|Number=Plur,Sing\|POS=VERB\|Person=1,2\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Case=Acc\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Fut\|VerbForm=Fin`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Fut\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Tot`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Number=Sing\|POS=VERB\|VerbForm=Fin`, `POS=VERB\|VerbForm=Fin`, `Degree=Abs\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Degree=Abs\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Ger`, `Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Dem`, `Definite=Ind\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Art`, `Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Acc,Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Gender=Masc\|Number=Sing\|POS=AUX\|VerbForm=Fin`, `POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Gender=Masc\|Number=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=PRON\|PronType=Int,Rel`, `Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Acc,Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Acc,Dat\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Ind`, `Mood=Ind\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Definite=Def\|Foreign=Yes\|POS=DET\|PronType=Art`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=PRON\|PronType=Dem`, `Gender=Fem\|Number=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=ADP\|PronType=Art`, `Case=Acc\|Number=Sing\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|PunctType=Quot\|VerbForm=Inf`, `Case=Dat\|Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Com\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Reflex=Yes`, `NumForm=Digit\|NumType=Frac\|POS=SYM`, `Number=Sing\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Dat\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Case=Dat\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Acc,Dat\|Gender=Masc\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Case=Acc,Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Ind`, `Case=Dat\|Number=Plur\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Acc\|Number=Plur\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Number=Sing\|POS=PRON\|PronType=Tot`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `POS=PRON\|PronType=Dem`, `Number=Sing\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `POS=AUX\|VerbForm=Fin`, `Gender=Fem\|NumType=Card\|Number=Plur\|POS=PRON\|PronType=Int,Rel`, `Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Case=Acc,Dat\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `AdvType=Tim\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|Typo=Yes\|VerbForm=Fin`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Acc\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs`, `Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Ind`, `Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person=2\|Poss=Yes\|PronType=Ind`, `Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=ADP\|PronType=Art`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=NOUN\|VerbForm=Part`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=AUX\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Case=Acc,Dat\|Number=Plur\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Gender=Masc\|Number=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Ind`, `Case=Acc\|Number=Sing\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Ger`, `Case=Acc,Dat\|Number=Sing\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes`, `Gender=Fem\|Number=Sing\|POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Com\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Pre\|PronType=Prs`, `POS=X`, `Case=Acc,Dat\|Number=Plur\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs`, `Case=Com\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Case=Acc,Dat\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Acc,Dat\|Number=Sing\|POS=PRON\|Person=1\|PrepCase=Npr\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Mood=Imp\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=2\|PrepCase=Npr\|PronType=Prs`, `Number=Sing\|POS=AUX\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Case=Acc\|Gender=Masc\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=PRON\|Person=2\|Poss=Yes\|PronType=Ind`, `Case=Dat\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=1,3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=2\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Inf`, `Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `POS=NOUN\|PunctType=Comm`, `Degree=Cmp\|POS=ADJ`, `Gender=Masc\|POS=ADJ`, `Degree=Abs\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=PRON\|PronType=Ind`, `POS=PRON\|PronType=Neg`, `Case=Acc,Dat\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Number=Plur\|POS=VERB\|Person=1\|PrepCase=Npr\|PronType=Prs\|Reflex=Yes\|VerbForm=Ger`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=3\|PrepCase=Npr\|PronType=Prs\|VerbForm=Ger`, `Gender=Fem\|Number=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Ind`, `Number=Sing\|POS=DET\|PronType=Int,Rel`, `Definite=Def\|Foreign=Yes\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Foreign=Yes\|POS=NOUN`, `Foreign=Yes\|POS=ADP`, `Foreign=Yes\|POS=CCONJ`, `Foreign=Yes\|POS=PROPN` | | **`parser`** | `ROOT`, `acl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `case`, `cc`, `ccomp`, `compound`, `conj`, `cop`, `csubj`, `dep`, `det`, `expl:impers`, `expl:pass`, `expl:pv`, `fixed`, `flat`, `iobj`, `mark`, `nmod`, `nsubj`, `nummod`, `obj`, `obl`, `parataxis`, `punct`, `xcomp` | | **`ner`** | `LOC`, `MISC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 100.00 | | `TOKEN_P` | 99.89 | | `TOKEN_R` | 99.95 | | `TOKEN_F` | 99.92 | | `POS_ACC` | 98.15 | | `MORPH_ACC` | 97.72 | | `MORPH_MICRO_P` | 99.24 | | `MORPH_MICRO_R` | 98.61 | | `MORPH_MICRO_F` | 98.93 | | `SENTS_P` | 96.30 | | `SENTS_R` | 98.15 | | `SENTS_F` | 97.22 | | `DEP_UAS` | 90.38 | | `DEP_LAS` | 86.85 | | `TAG_ACC` | 95.81 | | `LEMMA_ACC` | 96.30 | | `ENTS_P` | 89.10 | | `ENTS_R` | 89.18 | | `ENTS_F` | 89.14 |
spacy/fi_core_news_lg
spacy
2023-10-10T06:48:49Z
9
0
spacy
[ "spacy", "token-classification", "fi", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-05-02T09:12:58Z
--- tags: - spacy - token-classification language: - fi license: cc-by-sa-4.0 model-index: - name: fi_core_news_lg results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8236272879 - name: NER Recall type: recall value: 0.813030386 - name: NER F Score type: f_score value: 0.8182945309 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9709439124 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9628474502 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9221890983 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.8653065672 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8371365653 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.7941298453 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9083487941 --- ### Details: https://spacy.io/models/fi#fi_core_news_lg Finnish pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner. | Feature | Description | | --- | --- | | **Name** | `fi_core_news_lg` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | floret (200000, 300) | | **Sources** | [UD Finnish TDT v2.8](https://github.com/UniversalDependencies/UD_Finnish-TDT) (Ginter, Filip; Kanerva, Jenna; Laippala, Veronika; Miekka, Niko; Missilä, Anna; Ojala, Stina; Pyysalo, Sampo)<br />[TurkuONE (ffe2040e)](https://github.com/TurkuNLP/turku-one) (Jouni Luoma, Li-Hsin Chang, Filip Ginter, Sampo Pyysalo)<br />[Explosion Vectors (OSCAR 2109 + Wikipedia + OpenSubtitles + WMT News Crawl)](https://github.com/explosion/spacy-vectors-builder) (Explosion) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (2145 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `A`, `Adj`, `Adp`, `Adv`, `Adv_V`, `C`, `C_V`, `Foreign`, `Interj`, `N`, `Num`, `Pron`, `Punct`, `Symb`, `V`, `V_Pron`, `_SP` | | **`morphologizer`** | `Case=Nom\|Number=Sing\|POS=NOUN`, `NumType=Ord\|POS=ADJ`, `Case=Ade\|Number=Sing\|POS=NOUN`, `Case=Nom\|Derivation=U\|Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `POS=ADV`, `Case=Par\|Degree=Pos\|Number=Plur\|POS=ADJ`, `POS=CCONJ`, `Case=Par\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=Par\|Number=Plur\|POS=NOUN`, `Case=Ill\|Number=Sing\|POS=NOUN`, `POS=PUNCT`, `Case=Nom\|Degree=Pos\|Derivation=Lainen\|Number=Sing\|POS=ADJ`, `POS=SCONJ`, `Case=Nom\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Number=Sing\|POS=NOUN`, `Case=Abl\|Degree=Pos\|Derivation=Lainen\|Number=Sing\|POS=ADJ`, `Clitic=Kaan\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=0\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Derivation=Lainen\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=PROPN`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Dem`, `Clitic=Kin\|POS=ADV`, `Case=Gen\|Number=Plur\|POS=PROPN`, `Case=Ess\|Number=Sing\|POS=NOUN`, `Case=Ill\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Ela\|Derivation=Llinen,Vs\|Number=Sing\|POS=NOUN`, `POS=ADJ`, `Case=Gen\|Number=Plur\|POS=NOUN`, `Case=Par\|Number=Sing\|POS=PRON\|PronType=Dem`, `Number=Sing\|POS=AUX\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Ine\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Pass`, `Case=Ade\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Ins\|Number=Plur\|POS=NOUN`, `Case=Gen\|Number=Sing\|POS=PROPN`, `Case=Par\|Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Plur\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=All\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Ill\|InfForm=3\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Nom\|Clitic=Kin\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Number=Sing\|POS=NOUN\|Style=Coll`, `Case=All\|Derivation=U\|Number=Sing\|POS=NOUN`, `AdpType=Post\|POS=ADP`, `Case=Nom\|Degree=Pos\|Derivation=Llinen\|Number=Sing\|POS=ADJ`, `Case=Gen\|Number=Sing\|POS=PRON\|PronType=Rcp`, `Case=Abl\|Number=Sing\|POS=NOUN`, `Case=All\|Number=Sing\|POS=PRON\|PronType=Rcp`, `Case=Ine\|InfForm=3\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Par\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Par\|Derivation=Ja\|Number=Plur\|POS=NOUN`, `Case=Gen\|Derivation=Vs\|Number=Sing\|POS=NOUN`, `Case=Par\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Par\|Derivation=Ja\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Case=Tra\|Number=Sing\|POS=NOUN`, `Case=Ela\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Par\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Par\|Clitic=Kin\|Number=Sing\|POS=NOUN`, `InfForm=1\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Nom\|Derivation=Ja\|Number=Sing\|POS=NOUN`, `Case=Ela\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Ine\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `InfForm=1\|Number=Sing\|POS=AUX\|VerbForm=Inf\|Voice=Act`, `Derivation=Sti\|POS=ADV`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Ill\|Number=Sing\|POS=PRON\|PronType=Int`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=0\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ill\|Number=Plur\|POS=NOUN`, `Case=Par\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Agt\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Number=Plur\|POS=NOUN\|Person[psor]=3`, `Case=Par\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Ine\|Clitic=Kin\|Number=Plur\|POS=NOUN`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Gen\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=All\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Ill\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Par\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Derivation=Lainen\|Number=Sing\|POS=ADJ`, `Case=Gen\|Derivation=Inen\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Act`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=AUX\|PartForm=Pres\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Derivation=Ja\|Number=Plur\|POS=NOUN\|Typo=Yes`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Par\|Number=Sing\|POS=PRON\|Person[psor]=3\|Reflex=Yes`, `Case=All\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=All\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=All\|Number=Plur\|POS=NOUN`, `Case=Ela\|Derivation=U\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|Typo=Yes\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Clitic=Kaan\|Number=Sing\|POS=NOUN`, `Foreign=Yes\|POS=X`, `Clitic=Ka\|Number=Sing\|POS=AUX\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Ela\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Connegative=Yes\|Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Case=Tra\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=0\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Cmp\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Ade\|Number=Sing\|POS=PRON\|PronType=Rel`, `Mood=Ind\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=All\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=All\|Number=Plur\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Ind`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Clitic=Kin\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Par\|Derivation=Vs\|Number=Sing\|POS=NOUN`, `Case=Gen\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Ill\|Derivation=Ja\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Ine\|Number=Sing\|POS=PROPN`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=0\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Number=Sing\|POS=PRON`, `Case=Nom\|Derivation=Inen\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Ess\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Clitic=Ko\|Mood=Cnd\|Number=Plur\|POS=AUX\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Par\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Clitic=Ko\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=0\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ine\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ine\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1\|Style=Coll`, `Case=Ade\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Derivation=Ttain\|POS=ADV`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Pres\|Typo=Yes\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Clitic=Kin\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ine\|InfForm=2\|Number=Sing\|Number[psor]=Sing\|POS=VERB\|Person[psor]=1\|VerbForm=Inf\|Voice=Act`, `Case=All\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Ela\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Ela\|Number=Plur\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Ine\|Number=Plur\|POS=NOUN`, `Case=Com\|POS=NOUN\|Person[psor]=3`, `Case=Com\|POS=PRON\|Person[psor]=3\|PronType=Ind`, `Number[psor]=Sing\|POS=ADV\|Person[psor]=1`, `Case=Par\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person[psor]=1\|Reflex=Yes`, `Case=Par\|Number=Sing\|POS=PRON\|PronType=Int`, `Clitic=Ko\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Clitic=Ko\|Mood=Cnd\|Number=Sing\|POS=AUX\|Person=3\|VerbForm=Fin\|Voice=Act`, `POS=SPACE`, `Case=Ine\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Gen\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Derivation=Vs\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Par\|Derivation=Minen\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Derivation=Lainen\|Number=Plur\|POS=ADJ`, `Case=Ade\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Connegative=Yes\|Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Ill\|Degree=Cmp\|Number=Sing\|POS=ADJ`, `Number=Sing\|POS=SCONJ\|Person=1\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Par\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Par\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `AdpType=Post\|POS=ADP\|Person[psor]=3`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Derivation=Vs\|Number=Sing\|POS=NOUN`, `Case=Ill\|Degree=Pos\|Derivation=Ton\|Number=Plur\|POS=ADJ`, `Case=Ill\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=Nom\|Derivation=Minen\|Number=Sing\|POS=NOUN`, `Case=Ill\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=All\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Abbr=Yes\|Case=Ine\|Number=Sing\|POS=NOUN`, `Case=Ine\|InfForm=2\|Number=Sing\|Number[psor]=Sing\|POS=AUX\|Person[psor]=1\|VerbForm=Inf\|Voice=Act`, `Number=Sing\|POS=AUX\|Person=1\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Ela\|Number=Plur\|POS=NOUN`, `Case=Nom\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Par\|Degree=Cmp\|Number=Plur\|POS=ADJ`, `Case=Ine\|Number=Sing\|POS=PROPN\|Style=Coll`, `Abbr=Yes\|Case=Par\|Number=Sing\|POS=NOUN`, `Case=Ess\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Ess\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=AUX\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Ill\|Number=Sing\|POS=PROPN`, `Case=Par\|Degree=Pos\|Derivation=Llinen\|Number=Sing\|POS=ADJ`, `Case=Ine\|InfForm=2\|Number=Sing\|POS=VERB\|Person[psor]=3\|VerbForm=Inf\|Voice=Act`, `NumType=Card\|POS=NUM`, `Case=Tra\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ill\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=Ill\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Ins\|InfForm=2\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Gen\|Derivation=Lainen\|Number=Plur\|POS=NOUN`, `Case=Ela\|Derivation=Vs\|Number=Plur\|POS=NOUN`, `Case=Ade\|Number=Plur\|POS=NOUN`, `Case=Gen\|Number=Sing\|POS=NOUN\|Typo=Yes`, `Case=Ade\|InfForm=3\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Style=Coll\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Abl\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ade\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ill\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ela\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Ess\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ess\|Number=Sing\|POS=PRON\|Person[psor]=3\|Reflex=Yes`, `Case=Ade\|Number=Sing\|POS=PRON\|PronType=Dem`, `Connegative=Yes\|Mood=Ind\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `Clitic=Ko\|Number=Sing\|POS=SCONJ\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Par\|Number=Plur\|POS=PRON\|PronType=Dem`, `Connegative=Yes\|Mood=Cnd\|POS=AUX\|VerbForm=Fin`, `Case=Ela\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=Par\|Degree=Cmp\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Par\|Derivation=Llinen,Vs\|Number=Plur\|POS=NOUN`, `Case=Gen\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Gen\|Derivation=Ja\|Number=Sing\|POS=NOUN`, `Case=Par\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Agt\|VerbForm=Part\|Voice=Act`, `Mood=Imp\|Number=Sing\|POS=AUX\|Person=2\|VerbForm=Fin\|Voice=Act`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Act`, `POS=SYM`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Rel`, `Clitic=Ka\|Number=Plur\|POS=AUX\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Ela\|Number=Sing\|POS=PRON\|PronType=Dem`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=0\|VerbForm=Fin\|Voice=Act`, `Case=Ess\|Clitic=Kaan\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Ess\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=Gen\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Gen\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Sing\|POS=SCONJ\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Clitic=Kaan\|POS=ADV`, `Clitic=Pa\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ade\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Par\|Degree=Pos\|Derivation=Lainen\|Number=Sing\|POS=ADJ`, `Case=Ine\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Gen\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Ade\|Derivation=U\|Number=Sing\|POS=NOUN`, `Abbr=Yes\|POS=ADV`, `Case=Ine\|Degree=Pos\|Derivation=Ton\|Number=Sing\|POS=ADJ`, `Case=Par\|Degree=Pos\|Number=Plur\|Number[psor]=Sing\|POS=ADJ\|Person[psor]=1`, `Case=All\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Clitic=Kin\|Number=Sing\|POS=NOUN`, `POS=ADV\|Typo=Yes`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=Ela\|Derivation=Minen\|Number=Sing\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Ela\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Ela\|Degree=Pos\|Derivation=Llinen\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Derivation=Llinen\|Number=Sing\|POS=ADJ`, `Case=All\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ine\|Number=Plur\|POS=NOUN\|Person[psor]=3`, `Case=Par\|Derivation=U\|Number=Plur\|POS=NOUN`, `Case=Ela\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Clitic=Ko\|Mood=Cnd\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Par\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Pass`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=All\|Clitic=Kin\|Number=Sing\|POS=PROPN`, `Clitic=Kin\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|Derivation=Vs\|Number=Plur\|POS=NOUN\|Person[psor]=3`, `Case=All\|Number=Sing\|POS=PRON\|Person[psor]=3\|Reflex=Yes`, `AdpType=Prep\|POS=ADP`, `Case=Par\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=Ine\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs\|Style=Coll`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Rcp`, `Clitic=Ko\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Derivation=Vs\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs\|Style=Coll`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs\|Style=Coll`, `POS=INTJ`, `Case=Nom\|Derivation=Ja\|Number=Plur\|POS=NOUN`, `Case=Par\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ess\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Case=Ade\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs\|Style=Coll`, `Case=Ine\|InfForm=3\|Number=Sing\|POS=AUX\|VerbForm=Inf\|Voice=Act`, `Case=Gen\|Degree=Pos\|Number=Sing\|Number[psor]=Sing\|POS=VERB\|PartForm=Pres\|Person[psor]=1\|VerbForm=Part\|Voice=Act`, `Case=Ela\|Clitic=Kin\|Number=Sing\|POS=PRON\|PronType=Dem`, `Clitic=Kin\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ela\|Number=Plur\|POS=PRON\|PronType=Ind`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Ill\|Derivation=Inen,Vs\|Number=Sing\|POS=NOUN`, `Case=Ine\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Nom\|Clitic=Kin\|Number=Sing\|POS=PRON\|PronType=Rcp`, `Case=Par\|Derivation=Lainen\|Number=Sing\|POS=ADJ`, `Case=Ela\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Nom\|Number=Sing\|POS=NOUN\|Style=Coll`, `Case=Ine\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Ela\|Degree=Sup\|Number=Sing\|POS=ADJ`, `Case=Nom\|Clitic=Kin\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Abl\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=Ill\|Degree=Pos\|Number=Plur\|Number[psor]=Sing\|POS=VERB\|PartForm=Agt\|Person[psor]=1\|VerbForm=Part\|Voice=Act`, `Case=Abl\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Abl\|Derivation=Ja\|Number=Sing\|POS=NOUN`, `Case=Tra\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=Ill\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Abe\|InfForm=3\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Ade\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Tra\|Derivation=Ja\|Number=Sing\|POS=NOUN`, `Case=Ela\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ade\|Number=Sing\|POS=NOUN\|Person[psor]=3\|Typo=Yes`, `Case=Ela\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Nom\|Degree=Sup\|Number=Sing\|POS=ADJ`, `Clitic=Kin\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|Degree=Pos\|Derivation=Lainen\|Number=Plur\|POS=ADJ`, `Case=All\|Derivation=Ja\|Number=Sing\|POS=NOUN`, `Case=Gen\|Number=Plur\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Degree=Pos\|Derivation=Ton\|Number=Plur\|POS=ADJ`, `Case=All\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Abl\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Gen\|Derivation=Lainen\|Number=Sing\|POS=NOUN`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Act`, `Abbr=Yes\|Case=Nom\|Number=Sing\|POS=NOUN`, `Case=Nom\|Derivation=Vs\|Number=Plur\|POS=NOUN`, `Case=Par\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Clitic=Kin\|Mood=Cnd\|POS=AUX\|VerbForm=Fin\|Voice=Pass`, `Clitic=Han\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ela\|Degree=Sup\|Number=Plur\|POS=ADJ`, `Case=Par\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Number=Plur\|POS=PRON\|PronType=Ind`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ela\|Derivation=U\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Clitic=Han\|Number=Sing\|POS=PRON\|PronType=Ind`, `Abbr=Yes\|Case=Gen\|Number=Sing\|POS=PROPN`, `Clitic=Kin\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=All\|Derivation=Ja\|Number=Plur\|POS=NOUN`, `Clitic=Han\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=0\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Derivation=Sti\|POS=ADV\|Typo=Yes`, `Case=All\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Ill\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Gen\|Derivation=Minen\|Number=Sing\|POS=NOUN`, `Case=Nom\|Derivation=Tar\|Number=Sing\|POS=NOUN`, `Clitic=Ko\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Par\|Derivation=Minen\|Number=Plur\|POS=NOUN`, `Case=Ill\|Number=Plur\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Clitic=Kin\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Ess\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Pass`, `Case=Ill\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ\|Style=Coll`, `Case=Par\|Number=Plur\|POS=NOUN\|Person[psor]=3`, `Case=Nom\|Clitic=Kin\|Number=Sing\|POS=NOUN\|Style=Coll`, `Case=Ade\|Number=Sing\|POS=PROPN`, `Case=Nom\|Clitic=Han\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Ess\|Derivation=Inen\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Clitic=Ka\|Number=Sing\|POS=AUX\|Person=1\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Derivation=U\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=Nom\|Number=Plur\|POS=NOUN\|Style=Coll`, `Case=Ill\|Degree=Cmp\|Number=Plur\|POS=ADJ`, `Case=Nom\|Clitic=Kaan\|Degree=Pos\|Number=Sing\|POS=AUX\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Par\|Number=Plur\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Degree=Pos\|Derivation=Llinen\|Number=Plur\|POS=ADJ`, `Case=Par\|Number=Sing\|POS=PROPN`, `Number=Sing\|POS=VERB\|Person=0\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ela\|Number=Sing\|POS=PRON\|PronType=Prs\|Style=Coll`, `Case=Ela\|Number=Sing\|POS=PROPN`, `Case=Nom\|Clitic=Pa\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ade\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Par\|Degree=Pos\|Number=Plur\|POS=ADJ\|Typo=Yes`, `POS=ADV\|Style=Coll`, `Case=All\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person[psor]=1\|Reflex=Yes`, `Case=Tra\|Degree=Pos\|Derivation=Llinen\|Number=Sing\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Number=Plur\|Number[psor]=Sing\|POS=VERB\|PartForm=Agt\|Person[psor]=1\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Number=Plur\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=ADJ\|Person[psor]=3`, `Case=Par\|Degree=Pos\|Derivation=Llinen\|Number=Plur\|POS=ADJ`, `Mood=Ind\|POS=AUX\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=0\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=All\|Number=Sing\|POS=NOUN\|Style=Coll`, `Clitic=Han\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Number=Sing\|POS=PRON\|PronType=Dem\|Typo=Yes`, `Case=Ine\|Derivation=Vs\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Gen\|Degree=Sup\|Number=Sing\|POS=ADJ`, `Case=Par\|Degree=Pos\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Par\|Degree=Pos\|Derivation=Ton\|Number=Plur\|POS=ADJ`, `Case=Ine\|Number=Plur\|POS=PRON\|PronType=Dem`, `Number=Plur\|POS=AUX\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=AUX\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Gen\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=2`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Clitic=Kin\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Clitic=Kin\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ade\|Number=Plur\|POS=NOUN\|Person[psor]=3`, `Case=All\|Derivation=Vs\|Number=Plur\|POS=NOUN`, `Case=Par\|NumType=Card\|Number=Plur\|POS=NUM\|Typo=Yes`, `Clitic=Ko\|Number=Sing\|POS=AUX\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Clitic=Kin\|Connegative=Yes\|Mood=Ind\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `Case=Ill\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Ela\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Rcp`, `Abbr=Yes\|Case=Abl\|Number=Sing\|POS=PROPN`, `Case=Abl\|Number=Sing\|POS=PROPN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Case=Nom\|Clitic=Kin\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=ADJ\|Typo=Yes`, `Case=Ade\|Clitic=Kin\|Number=Sing\|POS=NOUN`, `Case=Ade\|Degree=Cmp\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Cmp\|Number=Sing\|POS=ADJ`, `Case=Ine\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Par\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Clitic=Kin\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Clitic=Kin\|Mood=Cnd\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|NumType=Card\|Number=Plur\|POS=NUM\|Typo=Yes`, `Case=Ess\|Number=Sing\|POS=PRON\|PronType=Dem`, `Clitic=Han\|POS=ADV`, `Case=Par\|Derivation=Llinen\|Number=Sing\|POS=ADJ`, `Case=Gen\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person[psor]=1\|Reflex=Yes`, `Case=Nom\|Clitic=Kin\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Par\|Derivation=Llinen\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Sing\|Number[psor]=Sing\|POS=VERB\|PartForm=Pres\|Person[psor]=1\|VerbForm=Part\|Voice=Act`, `Case=Abl\|Number=Plur\|POS=NOUN`, `Case=Abl\|Derivation=Lainen\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Pass`, `Case=All\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Par\|Derivation=Llinen,Vs\|Number=Sing\|POS=NOUN`, `Case=Ine\|Number=Plur\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Case=Ela\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Degree=Pos\|Derivation=Ton\|Number=Sing\|POS=ADJ`, `Case=Par\|Derivation=Ton,Vs\|Number=Sing\|POS=NOUN`, `Number=Plur\|POS=AUX\|Person=1\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Ill\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Ela\|InfForm=3\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Gen\|Derivation=Inen,Vs\|Number=Sing\|POS=NOUN`, `Case=All\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Gen\|Derivation=Llinen,Vs\|Number=Sing\|POS=NOUN`, `Case=Par\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Case=Par\|Degree=Pos\|Derivation=Ton\|Number=Sing\|POS=ADJ`, `Case=Tra\|InfForm=1\|Number=Sing\|POS=VERB\|Person[psor]=3\|VerbForm=Inf\|Voice=Act`, `Number=Sing\|POS=AUX\|Person=2\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Ill\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Case=All\|Derivation=Minen\|Number=Sing\|POS=NOUN`, `Abbr=Yes\|Case=Ade\|Number=Sing\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|Person[psor]=3\|VerbForm=Part\|Voice=Act`, `Case=Par\|Degree=Sup\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Derivation=Inen\|Number=Plur\|Number[psor]=Sing\|POS=ADJ\|Person[psor]=1`, `Case=Nom\|Clitic=Kin\|Degree=Cmp\|Number=Plur\|POS=ADJ`, `Clitic=Kaan\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|InfForm=2\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Ill\|Derivation=Vs\|Number=Plur\|POS=NOUN`, `Case=Par\|Derivation=Vs\|Number=Plur\|POS=NOUN`, `Case=Ill\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=All\|Number=Sing\|Number[psor]=Plur\|POS=PRON\|Person[psor]=1\|Reflex=Yes`, `Case=Nom\|Derivation=Llinen,Vs\|Number=Sing\|POS=NOUN`, `Number=Plur\|POS=SCONJ\|Person=1\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Number=Plur\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Case=Ela\|Degree=Pos\|Derivation=Lainen\|Number=Plur\|POS=ADJ`, `Case=Ill\|Number=Sing\|Number[psor]=Plur\|POS=PRON\|Person[psor]=1\|Reflex=Yes`, `Case=Ill\|Number=Plur\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Case=Ela\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=All\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Nom\|Clitic=Kin\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Clitic=Kin\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Past\|Typo=Yes\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Clitic=Kin\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Derivation=U\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Abl\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ess\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Ela\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ela\|Number=Sing\|Number[psor]=Plur\|POS=PRON\|Person[psor]=1\|Reflex=Yes`, `Case=Gen\|Derivation=Minen\|Number=Plur\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Par\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Pass`, `Clitic=Ko\|Number=Sing\|POS=VERB\|Person=0\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Ade\|InfForm=3\|Number=Sing\|POS=AUX\|VerbForm=Inf\|Voice=Act`, `Case=Gen\|Clitic=Han\|Number=Sing\|POS=NOUN`, `Case=Ill\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Ess\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=Ela\|Derivation=Vs\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Sing\|POS=PRON\|Reflex=Yes`, `Case=Par\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Clitic=Kaan\|Connegative=Yes\|Mood=Ind\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `Degree=Sup\|Derivation=Sti\|POS=ADV`, `Case=Ine\|Derivation=Llinen,Vs\|Number=Sing\|POS=NOUN`, `Case=Tra\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Pass`, `Case=Par\|Derivation=Inen,Vs\|Number=Plur\|POS=NOUN`, _(truncated: full list in pipeline meta)_ | | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `cc:preconj`, `ccomp`, `compound`, `compound:nn`, `compound:prt`, `conj`, `cop`, `cop:own`, `csubj`, `csubj:cop`, `dep`, `det`, `discourse`, `fixed`, `flat`, `flat:foreign`, `flat:name`, `mark`, `nmod`, `nmod:gobj`, `nmod:gsubj`, `nmod:poss`, `nsubj`, `nsubj:cop`, `nummod`, `obj`, `obl`, `orphan`, `parataxis`, `punct`, `vocative`, `xcomp`, `xcomp:ds` | | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 100.00 | | `TOKEN_P` | 99.79 | | `TOKEN_R` | 99.90 | | `TOKEN_F` | 99.85 | | `TAG_ACC` | 97.09 | | `POS_ACC` | 96.28 | | `MORPH_ACC` | 92.22 | | `MORPH_MICRO_P` | 96.26 | | `MORPH_MICRO_R` | 95.17 | | `MORPH_MICRO_F` | 95.71 | | `SENTS_P` | 91.96 | | `SENTS_R` | 89.74 | | `SENTS_F` | 90.83 | | `DEP_UAS` | 83.71 | | `DEP_LAS` | 79.41 | | `LEMMA_ACC` | 86.53 | | `ENTS_P` | 82.36 | | `ENTS_R` | 81.30 | | `ENTS_F` | 81.83 |
spacy/fi_core_news_md
spacy
2023-10-10T06:48:31Z
4
0
spacy
[ "spacy", "token-classification", "fi", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-05-02T09:12:33Z
--- tags: - spacy - token-classification language: - fi license: cc-by-sa-4.0 model-index: - name: fi_core_news_md results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8190770962 - name: NER Recall type: recall value: 0.7968792773 - name: NER F Score type: f_score value: 0.807825725 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9659361405 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9586650253 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9186882914 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.8602402419 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8321792131 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.7845751467 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.8935543278 --- ### Details: https://spacy.io/models/fi#fi_core_news_md Finnish pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner. | Feature | Description | | --- | --- | | **Name** | `fi_core_news_md` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | floret (50000, 300) | | **Sources** | [UD Finnish TDT v2.8](https://github.com/UniversalDependencies/UD_Finnish-TDT) (Ginter, Filip; Kanerva, Jenna; Laippala, Veronika; Miekka, Niko; Missilä, Anna; Ojala, Stina; Pyysalo, Sampo)<br />[TurkuONE (ffe2040e)](https://github.com/TurkuNLP/turku-one) (Jouni Luoma, Li-Hsin Chang, Filip Ginter, Sampo Pyysalo)<br />[Explosion Vectors (OSCAR 2109 + Wikipedia + OpenSubtitles + WMT News Crawl)](https://github.com/explosion/spacy-vectors-builder) (Explosion) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (2145 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `A`, `Adj`, `Adp`, `Adv`, `Adv_V`, `C`, `C_V`, `Foreign`, `Interj`, `N`, `Num`, `Pron`, `Punct`, `Symb`, `V`, `V_Pron`, `_SP` | | **`morphologizer`** | `Case=Nom\|Number=Sing\|POS=NOUN`, `NumType=Ord\|POS=ADJ`, `Case=Ade\|Number=Sing\|POS=NOUN`, `Case=Nom\|Derivation=U\|Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `POS=ADV`, `Case=Par\|Degree=Pos\|Number=Plur\|POS=ADJ`, `POS=CCONJ`, `Case=Par\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=Par\|Number=Plur\|POS=NOUN`, `Case=Ill\|Number=Sing\|POS=NOUN`, `POS=PUNCT`, `Case=Nom\|Degree=Pos\|Derivation=Lainen\|Number=Sing\|POS=ADJ`, `POS=SCONJ`, `Case=Nom\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Number=Sing\|POS=NOUN`, `Case=Abl\|Degree=Pos\|Derivation=Lainen\|Number=Sing\|POS=ADJ`, `Clitic=Kaan\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=0\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Derivation=Lainen\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=PROPN`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Dem`, `Clitic=Kin\|POS=ADV`, `Case=Gen\|Number=Plur\|POS=PROPN`, `Case=Ess\|Number=Sing\|POS=NOUN`, `Case=Ill\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Ela\|Derivation=Llinen,Vs\|Number=Sing\|POS=NOUN`, `POS=ADJ`, `Case=Gen\|Number=Plur\|POS=NOUN`, `Case=Par\|Number=Sing\|POS=PRON\|PronType=Dem`, `Number=Sing\|POS=AUX\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Ine\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Pass`, `Case=Ade\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Ins\|Number=Plur\|POS=NOUN`, `Case=Gen\|Number=Sing\|POS=PROPN`, `Case=Par\|Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Plur\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=All\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Ill\|InfForm=3\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Nom\|Clitic=Kin\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Number=Sing\|POS=NOUN\|Style=Coll`, `Case=All\|Derivation=U\|Number=Sing\|POS=NOUN`, `AdpType=Post\|POS=ADP`, `Case=Nom\|Degree=Pos\|Derivation=Llinen\|Number=Sing\|POS=ADJ`, `Case=Gen\|Number=Sing\|POS=PRON\|PronType=Rcp`, `Case=Abl\|Number=Sing\|POS=NOUN`, `Case=All\|Number=Sing\|POS=PRON\|PronType=Rcp`, `Case=Ine\|InfForm=3\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Par\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Par\|Derivation=Ja\|Number=Plur\|POS=NOUN`, `Case=Gen\|Derivation=Vs\|Number=Sing\|POS=NOUN`, `Case=Par\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Par\|Derivation=Ja\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Case=Tra\|Number=Sing\|POS=NOUN`, `Case=Ela\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Par\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Par\|Clitic=Kin\|Number=Sing\|POS=NOUN`, `InfForm=1\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Nom\|Derivation=Ja\|Number=Sing\|POS=NOUN`, `Case=Ela\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Ine\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `InfForm=1\|Number=Sing\|POS=AUX\|VerbForm=Inf\|Voice=Act`, `Derivation=Sti\|POS=ADV`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Ill\|Number=Sing\|POS=PRON\|PronType=Int`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=0\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ill\|Number=Plur\|POS=NOUN`, `Case=Par\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Agt\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Number=Plur\|POS=NOUN\|Person[psor]=3`, `Case=Par\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Ine\|Clitic=Kin\|Number=Plur\|POS=NOUN`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Gen\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Gen\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=All\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Ill\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Par\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Derivation=Lainen\|Number=Sing\|POS=ADJ`, `Case=Gen\|Derivation=Inen\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Act`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=AUX\|PartForm=Pres\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Derivation=Ja\|Number=Plur\|POS=NOUN\|Typo=Yes`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Par\|Number=Sing\|POS=PRON\|Person[psor]=3\|Reflex=Yes`, `Case=All\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=All\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=All\|Number=Plur\|POS=NOUN`, `Case=Ela\|Derivation=U\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|Typo=Yes\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Clitic=Kaan\|Number=Sing\|POS=NOUN`, `Foreign=Yes\|POS=X`, `Clitic=Ka\|Number=Sing\|POS=AUX\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Ela\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Connegative=Yes\|Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Case=Tra\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=0\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Cmp\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Ade\|Number=Sing\|POS=PRON\|PronType=Rel`, `Mood=Ind\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=All\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=All\|Number=Plur\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Ind`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Clitic=Kin\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Par\|Derivation=Vs\|Number=Sing\|POS=NOUN`, `Case=Gen\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Ill\|Derivation=Ja\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Ine\|Number=Sing\|POS=PROPN`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=0\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Number=Sing\|POS=PRON`, `Case=Nom\|Derivation=Inen\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Ess\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Clitic=Ko\|Mood=Cnd\|Number=Plur\|POS=AUX\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Par\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Clitic=Ko\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=0\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ine\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ine\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1\|Style=Coll`, `Case=Ade\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Derivation=Ttain\|POS=ADV`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Pres\|Typo=Yes\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Clitic=Kin\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ine\|InfForm=2\|Number=Sing\|Number[psor]=Sing\|POS=VERB\|Person[psor]=1\|VerbForm=Inf\|Voice=Act`, `Case=All\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Ela\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Ela\|Number=Plur\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Ine\|Number=Plur\|POS=NOUN`, `Case=Com\|POS=NOUN\|Person[psor]=3`, `Case=Com\|POS=PRON\|Person[psor]=3\|PronType=Ind`, `Number[psor]=Sing\|POS=ADV\|Person[psor]=1`, `Case=Par\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person[psor]=1\|Reflex=Yes`, `Case=Par\|Number=Sing\|POS=PRON\|PronType=Int`, `Clitic=Ko\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Clitic=Ko\|Mood=Cnd\|Number=Sing\|POS=AUX\|Person=3\|VerbForm=Fin\|Voice=Act`, `POS=SPACE`, `Case=Ine\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Gen\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Derivation=Vs\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Par\|Derivation=Minen\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Derivation=Lainen\|Number=Plur\|POS=ADJ`, `Case=Ade\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Connegative=Yes\|Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Ill\|Degree=Cmp\|Number=Sing\|POS=ADJ`, `Number=Sing\|POS=SCONJ\|Person=1\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Par\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Par\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `AdpType=Post\|POS=ADP\|Person[psor]=3`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Derivation=Vs\|Number=Sing\|POS=NOUN`, `Case=Ill\|Degree=Pos\|Derivation=Ton\|Number=Plur\|POS=ADJ`, `Case=Ill\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=Nom\|Derivation=Minen\|Number=Sing\|POS=NOUN`, `Case=Ill\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=All\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Abbr=Yes\|Case=Ine\|Number=Sing\|POS=NOUN`, `Case=Ine\|InfForm=2\|Number=Sing\|Number[psor]=Sing\|POS=AUX\|Person[psor]=1\|VerbForm=Inf\|Voice=Act`, `Number=Sing\|POS=AUX\|Person=1\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Ela\|Number=Plur\|POS=NOUN`, `Case=Nom\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Par\|Degree=Cmp\|Number=Plur\|POS=ADJ`, `Case=Ine\|Number=Sing\|POS=PROPN\|Style=Coll`, `Abbr=Yes\|Case=Par\|Number=Sing\|POS=NOUN`, `Case=Ess\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Ess\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=AUX\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Ill\|Number=Sing\|POS=PROPN`, `Case=Par\|Degree=Pos\|Derivation=Llinen\|Number=Sing\|POS=ADJ`, `Case=Ine\|InfForm=2\|Number=Sing\|POS=VERB\|Person[psor]=3\|VerbForm=Inf\|Voice=Act`, `NumType=Card\|POS=NUM`, `Case=Tra\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ill\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=Ill\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Ins\|InfForm=2\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Gen\|Derivation=Lainen\|Number=Plur\|POS=NOUN`, `Case=Ela\|Derivation=Vs\|Number=Plur\|POS=NOUN`, `Case=Ade\|Number=Plur\|POS=NOUN`, `Case=Gen\|Number=Sing\|POS=NOUN\|Typo=Yes`, `Case=Ade\|InfForm=3\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Style=Coll\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Abl\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ade\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ill\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ela\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Ess\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ess\|Number=Sing\|POS=PRON\|Person[psor]=3\|Reflex=Yes`, `Case=Ade\|Number=Sing\|POS=PRON\|PronType=Dem`, `Connegative=Yes\|Mood=Ind\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `Clitic=Ko\|Number=Sing\|POS=SCONJ\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Par\|Number=Plur\|POS=PRON\|PronType=Dem`, `Connegative=Yes\|Mood=Cnd\|POS=AUX\|VerbForm=Fin`, `Case=Ela\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=Par\|Degree=Cmp\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Par\|Derivation=Llinen,Vs\|Number=Plur\|POS=NOUN`, `Case=Gen\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Gen\|Derivation=Ja\|Number=Sing\|POS=NOUN`, `Case=Par\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Agt\|VerbForm=Part\|Voice=Act`, `Mood=Imp\|Number=Sing\|POS=AUX\|Person=2\|VerbForm=Fin\|Voice=Act`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Act`, `POS=SYM`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Rel`, `Clitic=Ka\|Number=Plur\|POS=AUX\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Ela\|Number=Sing\|POS=PRON\|PronType=Dem`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=0\|VerbForm=Fin\|Voice=Act`, `Case=Ess\|Clitic=Kaan\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Ess\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=Gen\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Gen\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Sing\|POS=SCONJ\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Clitic=Kaan\|POS=ADV`, `Clitic=Pa\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ade\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Par\|Degree=Pos\|Derivation=Lainen\|Number=Sing\|POS=ADJ`, `Case=Ine\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Gen\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Ade\|Derivation=U\|Number=Sing\|POS=NOUN`, `Abbr=Yes\|POS=ADV`, `Case=Ine\|Degree=Pos\|Derivation=Ton\|Number=Sing\|POS=ADJ`, `Case=Par\|Degree=Pos\|Number=Plur\|Number[psor]=Sing\|POS=ADJ\|Person[psor]=1`, `Case=All\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Clitic=Kin\|Number=Sing\|POS=NOUN`, `POS=ADV\|Typo=Yes`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=Ela\|Derivation=Minen\|Number=Sing\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Ela\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Ela\|Degree=Pos\|Derivation=Llinen\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Derivation=Llinen\|Number=Sing\|POS=ADJ`, `Case=All\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ine\|Number=Plur\|POS=NOUN\|Person[psor]=3`, `Case=Par\|Derivation=U\|Number=Plur\|POS=NOUN`, `Case=Ela\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Clitic=Ko\|Mood=Cnd\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Act`, `Case=Par\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Pass`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=All\|Clitic=Kin\|Number=Sing\|POS=PROPN`, `Clitic=Kin\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|Derivation=Vs\|Number=Plur\|POS=NOUN\|Person[psor]=3`, `Case=All\|Number=Sing\|POS=PRON\|Person[psor]=3\|Reflex=Yes`, `AdpType=Prep\|POS=ADP`, `Case=Par\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=Ine\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs\|Style=Coll`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Rcp`, `Clitic=Ko\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Derivation=Vs\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs\|Style=Coll`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs\|Style=Coll`, `POS=INTJ`, `Case=Nom\|Derivation=Ja\|Number=Plur\|POS=NOUN`, `Case=Par\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ess\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Case=Ade\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs\|Style=Coll`, `Case=Ine\|InfForm=3\|Number=Sing\|POS=AUX\|VerbForm=Inf\|Voice=Act`, `Case=Gen\|Degree=Pos\|Number=Sing\|Number[psor]=Sing\|POS=VERB\|PartForm=Pres\|Person[psor]=1\|VerbForm=Part\|Voice=Act`, `Case=Ela\|Clitic=Kin\|Number=Sing\|POS=PRON\|PronType=Dem`, `Clitic=Kin\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ela\|Number=Plur\|POS=PRON\|PronType=Ind`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Ill\|Derivation=Inen,Vs\|Number=Sing\|POS=NOUN`, `Case=Ine\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Nom\|Clitic=Kin\|Number=Sing\|POS=PRON\|PronType=Rcp`, `Case=Par\|Derivation=Lainen\|Number=Sing\|POS=ADJ`, `Case=Ela\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Nom\|Number=Sing\|POS=NOUN\|Style=Coll`, `Case=Ine\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Ela\|Degree=Sup\|Number=Sing\|POS=ADJ`, `Case=Nom\|Clitic=Kin\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Abl\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=Ill\|Degree=Pos\|Number=Plur\|Number[psor]=Sing\|POS=VERB\|PartForm=Agt\|Person[psor]=1\|VerbForm=Part\|Voice=Act`, `Case=Abl\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Abl\|Derivation=Ja\|Number=Sing\|POS=NOUN`, `Case=Tra\|Derivation=U\|Number=Sing\|POS=NOUN`, `Case=Ill\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Abe\|InfForm=3\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Ade\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Tra\|Derivation=Ja\|Number=Sing\|POS=NOUN`, `Case=Ela\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ade\|Number=Sing\|POS=NOUN\|Person[psor]=3\|Typo=Yes`, `Case=Ela\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Nom\|Degree=Sup\|Number=Sing\|POS=ADJ`, `Clitic=Kin\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|Degree=Pos\|Derivation=Lainen\|Number=Plur\|POS=ADJ`, `Case=All\|Derivation=Ja\|Number=Sing\|POS=NOUN`, `Case=Gen\|Number=Plur\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Degree=Pos\|Derivation=Ton\|Number=Plur\|POS=ADJ`, `Case=All\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Abl\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Gen\|Derivation=Lainen\|Number=Sing\|POS=NOUN`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Act`, `Abbr=Yes\|Case=Nom\|Number=Sing\|POS=NOUN`, `Case=Nom\|Derivation=Vs\|Number=Plur\|POS=NOUN`, `Case=Par\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Clitic=Kin\|Mood=Cnd\|POS=AUX\|VerbForm=Fin\|Voice=Pass`, `Clitic=Han\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ela\|Degree=Sup\|Number=Plur\|POS=ADJ`, `Case=Par\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Number=Plur\|POS=PRON\|PronType=Ind`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ela\|Derivation=U\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Clitic=Han\|Number=Sing\|POS=PRON\|PronType=Ind`, `Abbr=Yes\|Case=Gen\|Number=Sing\|POS=PROPN`, `Clitic=Kin\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=All\|Derivation=Ja\|Number=Plur\|POS=NOUN`, `Clitic=Han\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=0\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Derivation=Sti\|POS=ADV\|Typo=Yes`, `Case=All\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Ill\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Gen\|Derivation=Minen\|Number=Sing\|POS=NOUN`, `Case=Nom\|Derivation=Tar\|Number=Sing\|POS=NOUN`, `Clitic=Ko\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Par\|Derivation=Minen\|Number=Plur\|POS=NOUN`, `Case=Ill\|Number=Plur\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Clitic=Kin\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Ess\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Pass`, `Case=Ill\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ\|Style=Coll`, `Case=Par\|Number=Plur\|POS=NOUN\|Person[psor]=3`, `Case=Nom\|Clitic=Kin\|Number=Sing\|POS=NOUN\|Style=Coll`, `Case=Ade\|Number=Sing\|POS=PROPN`, `Case=Nom\|Clitic=Han\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Ess\|Derivation=Inen\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Clitic=Ka\|Number=Sing\|POS=AUX\|Person=1\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Derivation=U\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=Nom\|Number=Plur\|POS=NOUN\|Style=Coll`, `Case=Ill\|Degree=Cmp\|Number=Plur\|POS=ADJ`, `Case=Nom\|Clitic=Kaan\|Degree=Pos\|Number=Sing\|POS=AUX\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Par\|Number=Plur\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Degree=Pos\|Derivation=Llinen\|Number=Plur\|POS=ADJ`, `Case=Par\|Number=Sing\|POS=PROPN`, `Number=Sing\|POS=VERB\|Person=0\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ela\|Number=Sing\|POS=PRON\|PronType=Prs\|Style=Coll`, `Case=Ela\|Number=Sing\|POS=PROPN`, `Case=Nom\|Clitic=Pa\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ade\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Par\|Degree=Pos\|Number=Plur\|POS=ADJ\|Typo=Yes`, `POS=ADV\|Style=Coll`, `Case=All\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person[psor]=1\|Reflex=Yes`, `Case=Tra\|Degree=Pos\|Derivation=Llinen\|Number=Sing\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Number=Plur\|Number[psor]=Sing\|POS=VERB\|PartForm=Agt\|Person[psor]=1\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Number=Plur\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=ADJ\|Person[psor]=3`, `Case=Par\|Degree=Pos\|Derivation=Llinen\|Number=Plur\|POS=ADJ`, `Mood=Ind\|POS=AUX\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=0\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=All\|Number=Sing\|POS=NOUN\|Style=Coll`, `Clitic=Han\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Number=Sing\|POS=PRON\|PronType=Dem\|Typo=Yes`, `Case=Ine\|Derivation=Vs\|Number=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Gen\|Degree=Sup\|Number=Sing\|POS=ADJ`, `Case=Par\|Degree=Pos\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Par\|Degree=Pos\|Derivation=Ton\|Number=Plur\|POS=ADJ`, `Case=Ine\|Number=Plur\|POS=PRON\|PronType=Dem`, `Number=Plur\|POS=AUX\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=AUX\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Gen\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=2`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Clitic=Kin\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Clitic=Kin\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ade\|Number=Plur\|POS=NOUN\|Person[psor]=3`, `Case=All\|Derivation=Vs\|Number=Plur\|POS=NOUN`, `Case=Par\|NumType=Card\|Number=Plur\|POS=NUM\|Typo=Yes`, `Clitic=Ko\|Number=Sing\|POS=AUX\|Person=3\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Clitic=Kin\|Connegative=Yes\|Mood=Ind\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `Case=Ill\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Ela\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Nom\|Number=Plur\|POS=PRON\|PronType=Rcp`, `Abbr=Yes\|Case=Abl\|Number=Sing\|POS=PROPN`, `Case=Abl\|Number=Sing\|POS=PROPN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Case=Nom\|Clitic=Kin\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=ADJ\|Typo=Yes`, `Case=Ade\|Clitic=Kin\|Number=Sing\|POS=NOUN`, `Case=Ade\|Degree=Cmp\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Cmp\|Number=Sing\|POS=ADJ`, `Case=Ine\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Par\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Clitic=Kin\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Clitic=Kin\|Mood=Cnd\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|NumType=Card\|Number=Plur\|POS=NUM\|Typo=Yes`, `Case=Ess\|Number=Sing\|POS=PRON\|PronType=Dem`, `Clitic=Han\|POS=ADV`, `Case=Par\|Derivation=Llinen\|Number=Sing\|POS=ADJ`, `Case=Gen\|Number=Sing\|Number[psor]=Sing\|POS=PRON\|Person[psor]=1\|Reflex=Yes`, `Case=Nom\|Clitic=Kin\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Par\|Derivation=Llinen\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Sing\|Number[psor]=Sing\|POS=VERB\|PartForm=Pres\|Person[psor]=1\|VerbForm=Part\|Voice=Act`, `Case=Abl\|Number=Plur\|POS=NOUN`, `Case=Abl\|Derivation=Lainen\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Pass`, `Case=All\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Par\|Derivation=Llinen,Vs\|Number=Sing\|POS=NOUN`, `Case=Ine\|Number=Plur\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Case=Ela\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Case=Nom\|Degree=Pos\|Derivation=Ton\|Number=Sing\|POS=ADJ`, `Case=Par\|Derivation=Ton,Vs\|Number=Sing\|POS=NOUN`, `Number=Plur\|POS=AUX\|Person=1\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Ill\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Ela\|InfForm=3\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Gen\|Derivation=Inen,Vs\|Number=Sing\|POS=NOUN`, `Case=All\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Gen\|Derivation=Llinen,Vs\|Number=Sing\|POS=NOUN`, `Case=Par\|Number=Sing\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Case=Par\|Degree=Pos\|Derivation=Ton\|Number=Sing\|POS=ADJ`, `Case=Tra\|InfForm=1\|Number=Sing\|POS=VERB\|Person[psor]=3\|VerbForm=Inf\|Voice=Act`, `Number=Sing\|POS=AUX\|Person=2\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Ill\|Degree=Pos\|Derivation=Inen\|Number=Sing\|POS=ADJ`, `Case=All\|Derivation=Minen\|Number=Sing\|POS=NOUN`, `Abbr=Yes\|Case=Ade\|Number=Sing\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|Person[psor]=3\|VerbForm=Part\|Voice=Act`, `Case=Par\|Degree=Sup\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Derivation=Inen\|Number=Plur\|Number[psor]=Sing\|POS=ADJ\|Person[psor]=1`, `Case=Nom\|Clitic=Kin\|Degree=Cmp\|Number=Plur\|POS=ADJ`, `Clitic=Kaan\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ine\|InfForm=2\|Number=Sing\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Ill\|Derivation=Vs\|Number=Plur\|POS=NOUN`, `Case=Par\|Derivation=Vs\|Number=Plur\|POS=NOUN`, `Case=Ill\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=All\|Number=Sing\|Number[psor]=Plur\|POS=PRON\|Person[psor]=1\|Reflex=Yes`, `Case=Nom\|Derivation=Llinen,Vs\|Number=Sing\|POS=NOUN`, `Number=Plur\|POS=SCONJ\|Person=1\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Number=Plur\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Case=Ela\|Degree=Pos\|Derivation=Lainen\|Number=Plur\|POS=ADJ`, `Case=Ill\|Number=Sing\|Number[psor]=Plur\|POS=PRON\|Person[psor]=1\|Reflex=Yes`, `Case=Ill\|Number=Plur\|Number[psor]=Plur\|POS=NOUN\|Person[psor]=1`, `Case=Ela\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=All\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Nom\|Clitic=Kin\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Clitic=Kin\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Past\|Typo=Yes\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Clitic=Kin\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Derivation=U\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=1`, `Case=Abl\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ess\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Ela\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ela\|Number=Sing\|Number[psor]=Plur\|POS=PRON\|Person[psor]=1\|Reflex=Yes`, `Case=Gen\|Derivation=Minen\|Number=Plur\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Case=Par\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Pres\|VerbForm=Part\|Voice=Pass`, `Clitic=Ko\|Number=Sing\|POS=VERB\|Person=0\|Polarity=Neg\|VerbForm=Fin\|Voice=Act`, `Case=Ade\|InfForm=3\|Number=Sing\|POS=AUX\|VerbForm=Inf\|Voice=Act`, `Case=Gen\|Clitic=Han\|Number=Sing\|POS=NOUN`, `Case=Ill\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Ess\|Degree=Pos\|Derivation=Inen\|Number=Plur\|POS=ADJ`, `Case=Ela\|Derivation=Vs\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Sing\|POS=PRON\|Reflex=Yes`, `Case=Par\|Degree=Pos\|Number=Sing\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Act`, `Clitic=Kaan\|Connegative=Yes\|Mood=Ind\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `Degree=Sup\|Derivation=Sti\|POS=ADV`, `Case=Ine\|Derivation=Llinen,Vs\|Number=Sing\|POS=NOUN`, `Case=Tra\|Degree=Pos\|Number=Plur\|POS=VERB\|PartForm=Past\|VerbForm=Part\|Voice=Pass`, `Case=Par\|Derivation=Inen,Vs\|Number=Plur\|POS=NOUN`, _(truncated: full list in pipeline meta)_ | | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `cc:preconj`, `ccomp`, `compound`, `compound:nn`, `compound:prt`, `conj`, `cop`, `cop:own`, `csubj`, `csubj:cop`, `dep`, `det`, `discourse`, `fixed`, `flat`, `flat:foreign`, `flat:name`, `mark`, `nmod`, `nmod:gobj`, `nmod:gsubj`, `nmod:poss`, `nsubj`, `nsubj:cop`, `nummod`, `obj`, `obl`, `orphan`, `parataxis`, `punct`, `vocative`, `xcomp`, `xcomp:ds` | | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 100.00 | | `TOKEN_P` | 99.79 | | `TOKEN_R` | 99.90 | | `TOKEN_F` | 99.85 | | `TAG_ACC` | 96.59 | | `POS_ACC` | 95.87 | | `MORPH_ACC` | 91.87 | | `MORPH_MICRO_P` | 95.90 | | `MORPH_MICRO_R` | 94.93 | | `MORPH_MICRO_F` | 95.41 | | `SENTS_P` | 89.79 | | `SENTS_R` | 88.93 | | `SENTS_F` | 89.36 | | `DEP_UAS` | 83.22 | | `DEP_LAS` | 78.46 | | `LEMMA_ACC` | 86.02 | | `ENTS_P` | 81.91 | | `ENTS_R` | 79.69 | | `ENTS_F` | 80.78 |
spacy/fr_core_news_lg
spacy
2023-10-10T06:48:21Z
36
2
spacy
[ "spacy", "token-classification", "fr", "license:lgpl-lr", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - fr license: lgpl-lr model-index: - name: fr_core_news_lg results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8398572946 - name: NER Recall type: recall value: 0.83869741 - name: NER F Score type: f_score value: 0.8392769516 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9446562919 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9734102855 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9674260386 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9135840526 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.9028935185 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8654090962 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.8735083532 --- ### Details: https://spacy.io/models/fr#fr_core_news_lg French pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer. | Feature | Description | | --- | --- | | **Name** | `fr_core_news_lg` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` | | **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) | | **Sources** | [UD French Sequoia v2.8](https://github.com/UniversalDependencies/UD_French-Sequoia) (Candito, Marie; Seddah, Djamé; Perrier, Guy; Guillaume, Bruno)<br />[WikiNER](https://figshare.com/articles/Learning_multilingual_named_entity_recognition_from_Wikipedia/5462500) (Joel Nothman, Nicky Ringland, Will Radford, Tara Murphy, James R Curran)<br />[spaCy lookups data](https://github.com/explosion/spacy-lookups-data) (Explosion)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `LGPL-LR` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (237 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `POS=PROPN`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Fem\|Number=Sing\|POS=NOUN`, `Number=Plur\|POS=PRON\|Person=1`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `POS=SCONJ`, `POS=ADP`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `NumType=Ord\|POS=ADJ`, `Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=PUNCT`, `Gender=Masc\|Number=Sing\|POS=PROPN`, `Number=Plur\|POS=ADJ`, `Gender=Masc\|Number=Plur\|POS=NOUN`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `POS=ADV`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Fem\|Number=Sing\|POS=PROPN`, `Definite=Def\|Number=Sing\|POS=DET\|PronType=Art`, `NumType=Card\|POS=NUM`, `Definite=Def\|Number=Plur\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Plur\|POS=ADJ`, `POS=CCONJ`, `Gender=Fem\|Number=Plur\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Gender=Fem\|Number=Plur\|POS=ADJ`, `POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `POS=PRON\|PronType=Rel`, `Number=Sing\|POS=DET\|Poss=Yes`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=ADP\|PronType=Art`, `Definite=Def\|Number=Plur\|POS=ADP\|PronType=Art`, `Definite=Ind\|Number=Plur\|POS=DET\|PronType=Art`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `POS=VERB\|VerbForm=Inf`, `Gender=Fem\|Number=Sing\|POS=ADJ`, `Gender=Masc\|Number=Sing\|POS=PRON\|Person=3`, `Number=Plur\|POS=DET`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=ADJ`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `POS=ADV\|PronType=Int`, `POS=VERB\|Tense=Pres\|VerbForm=Part`, `Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Number=Plur\|POS=DET\|Poss=Yes`, `POS=AUX\|VerbForm=Inf`, `Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Gender=Masc\|POS=VERB\|Tense=Past\|VerbForm=Part`, `POS=ADV\|Polarity=Neg`, `Definite=Ind\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Fem\|Number=Sing\|POS=PRON\|Person=3`, `POS=PRON\|Person=3\|Reflex=Yes`, `Gender=Masc\|POS=NOUN`, `POS=AUX\|Tense=Past\|VerbForm=Part`, `POS=PRON\|Person=3`, `Number=Plur\|POS=NOUN`, `NumType=Ord\|Number=Sing\|POS=ADJ`, `POS=VERB\|Tense=Past\|VerbForm=Part`, `POS=AUX\|Tense=Pres\|VerbForm=Part`, `Gender=Masc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Number=Sing\|POS=PRON\|Person=3`, `Number=Sing\|POS=NOUN`, `Gender=Masc\|Number=Plur\|POS=PRON\|Person=3`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Number=Plur\|POS=PROPN`, `Number=Sing\|POS=PROPN`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=DET`, `Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes`, `Gender=Masc\|POS=PRON`, `POS=NOUN`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Number=Plur\|POS=PRON`, `Gender=Masc\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Number=Sing\|POS=PRON`, `Number=Sing\|POS=PRON\|PronType=Dem`, `Mood=Ind\|POS=VERB\|VerbForm=Fin`, `Number=Plur\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=PRON`, `Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Rel`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|NumType=Ord\|Number=Sing\|POS=ADJ`, `POS=PRON`, `POS=NUM`, `Gender=Fem\|POS=NOUN`, `POS=SPACE`, `Gender=Fem\|Number=Plur\|POS=PRON`, `Number=Plur\|POS=PRON\|Person=3`, `Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Number=Sing\|POS=PRON\|Person=1`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=PRON`, `Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `POS=INTJ`, `Number=Plur\|POS=PRON\|Person=2`, `NumType=Card\|POS=PRON`, `Definite=Ind\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Gender=Fem\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `NumType=Card\|POS=NOUN`, `POS=PRON\|PronType=Int`, `Gender=Fem\|Number=Plur\|POS=PRON\|Person=3`, `Gender=Fem\|Number=Sing\|POS=DET`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=DET`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Definite=Ind\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Gender=Masc\|Number=Plur\|POS=PROPN`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Number=Sing\|POS=DET`, `Gender=Masc\|NumType=Card\|Number=Plur\|POS=NOUN`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Dem`, `Mood=Ind\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|POS=PRON`, `Gender=Masc\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Rel`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part`, `POS=X`, `POS=SYM`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int`, `POS=DET`, `Gender=Masc\|Number=Plur\|POS=PRON`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|POS=VERB\|Person=3\|VerbForm=Fin`, `Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `Gender=Masc\|Number=Plur\|POS=DET`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Rel`, `Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Rel`, `POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Gender=Fem\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Fut\|VerbForm=Fin`, `Mood=Imp\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=2\|Reflex=Yes`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=1\|Reflex=Yes`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Number=Sing\|POS=PRON\|Person=1\|Reflex=Yes`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|POS=PROPN`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Imp\|VerbForm=Fin`, `Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Gender=Fem\|Number=Plur\|POS=PROPN`, `Gender=Masc\|NumType=Card\|POS=NUM` | | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux:pass`, `aux:tense`, `case`, `cc`, `ccomp`, `conj`, `cop`, `dep`, `det`, `expl:comp`, `expl:pass`, `expl:subj`, `fixed`, `flat:foreign`, `flat:name`, `iobj`, `mark`, `nmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl:agent`, `obl:arg`, `obl:mod`, `parataxis`, `punct`, `vocative`, `xcomp` | | **`ner`** | `LOC`, `MISC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.80 | | `TOKEN_P` | 98.44 | | `TOKEN_R` | 98.96 | | `TOKEN_F` | 98.70 | | `POS_ACC` | 97.34 | | `MORPH_ACC` | 96.74 | | `MORPH_MICRO_P` | 98.91 | | `MORPH_MICRO_R` | 98.17 | | `MORPH_MICRO_F` | 98.54 | | `SENTS_P` | 85.92 | | `SENTS_R` | 89.26 | | `SENTS_F` | 87.35 | | `DEP_UAS` | 90.29 | | `DEP_LAS` | 86.54 | | `TAG_ACC` | 94.47 | | `LEMMA_ACC` | 91.36 | | `ENTS_P` | 83.99 | | `ENTS_R` | 83.87 | | `ENTS_F` | 83.93 |
spacy/hr_core_news_lg
spacy
2023-10-10T06:47:24Z
10
0
spacy
[ "spacy", "token-classification", "hr", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-07-20T08:07:47Z
--- tags: - spacy - token-classification language: - hr license: cc-by-sa-4.0 model-index: - name: hr_core_news_lg results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8309481216 - name: NER Recall type: recall value: 0.8294642857 - name: NER F Score type: f_score value: 0.8302055407 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9217400961 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9759146596 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9267547757 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9287546545 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8661791243 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8015566665 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9454545455 --- ### Details: https://spacy.io/models/hr#hr_core_news_lg Croatian pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner. | Feature | Description | | --- | --- | | **Name** | `hr_core_news_lg` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | floret (200000, 300) | | **Sources** | [Training corpus hr500k 1.0](http://hdl.handle.net/11356/1183) (Ljubešić, Nikola ; Agić, Željko ; Klubička, Filip ; Batanović, Vuk and Erjavec, Tomaž)<br />[Explosion Vectors (OSCAR 2109 + Wikipedia + OpenSubtitles + WMT News Crawl)](https://github.com/explosion/spacy-vectors-builder) (Explosion) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (1518 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `Agcfpay`, `Agcfpdy`, `Agcfpgy`, `Agcfpiy`, `Agcfply`, `Agcfpny`, `Agcfsay`, `Agcfsdy`, `Agcfsgy`, `Agcfsiy`, `Agcfsly`, `Agcfsny`, `Agcmpay`, `Agcmpgy`, `Agcmpiy`, `Agcmpny`, `Agcmsany`, `Agcmsay`, `Agcmsayn`, `Agcmsdy`, `Agcmsgy`, `Agcmsiy`, `Agcmsly`, `Agcmsny`, `Agcnpay`, `Agcnpdy`, `Agcnpgy`, `Agcnpny`, `Agcnsay`, `Agcnsdy`, `Agcnsgy`, `Agcnsiy`, `Agcnsly`, `Agcnsny`, `Agpfpay`, `Agpfpdy`, `Agpfpgy`, `Agpfpiy`, `Agpfply`, `Agpfpny`, `Agpfsay`, `Agpfsdy`, `Agpfsgy`, `Agpfsin`, `Agpfsiy`, `Agpfsly`, `Agpfsny`, `Agpfsvy`, `Agpmpay`, `Agpmpdy`, `Agpmpgy`, `Agpmpiy`, `Agpmply`, `Agpmpny`, `Agpmsan`, `Agpmsann`, `Agpmsany`, `Agpmsay`, `Agpmsayn`, `Agpmsayy`, `Agpmsdy`, `Agpmsgn`, `Agpmsgy`, `Agpmsiy`, `Agpmsln`, `Agpmsly`, `Agpmsnn`, `Agpmsny`, `Agpmsvy`, `Agpnpay`, `Agpnpdy`, `Agpnpgy`, `Agpnpiy`, `Agpnply`, `Agpnpny`, `Agpnsay`, `Agpnsdy`, `Agpnsgn`, `Agpnsgy`, `Agpnsiy`, `Agpnsln`, `Agpnsly`, `Agpnsny`, `Agsfpay`, `Agsfpdy`, `Agsfpgy`, `Agsfpiy`, `Agsfply`, `Agsfpny`, `Agsfsay`, `Agsfsdy`, `Agsfsgy`, `Agsfsiy`, `Agsfsly`, `Agsfsny`, `Agsmpay`, `Agsmpdy`, `Agsmpgy`, `Agsmpiy`, `Agsmply`, `Agsmpny`, `Agsmsany`, `Agsmsayn`, `Agsmsayy`, `Agsmsdy`, `Agsmsgy`, `Agsmsiy`, `Agsmsly`, `Agsmsny`, `Agsnpay`, `Agsnpgy`, `Agsnply`, `Agsnpny`, `Agsnsay`, `Agsnsdy`, `Agsnsgy`, `Agsnsiy`, `Agsnsly`, `Agsnsny`, `Appfpay`, `Appfpdy`, `Appfpgy`, `Appfpiy`, `Appfply`, `Appfpny`, `Appfsay`, `Appfsgy`, `Appfsiy`, `Appfsly`, `Appfsny`, `Appmpay`, `Appmpdy`, `Appmpgy`, `Appmpiy`, `Appmply`, `Appmpny`, `Appmsann`, `Appmsany`, `Appmsayn`, `Appmsayy`, `Appmsdy`, `Appmsgn`, `Appmsgy`, `Appmsiy`, `Appmsly`, `Appmsnn`, `Appmsny`, `Appnpay`, `Appnpdy`, `Appnpgy`, `Appnpiy`, `Appnply`, `Appnpny`, `Appnsay`, `Appnsgy`, `Appnsly`, `Appnsny`, `Aspfpay`, `Aspfpgy`, `Aspfpiy`, `Aspfply`, `Aspfpny`, `Aspfsay`, `Aspfsdy`, `Aspfsgy`, `Aspfsly`, `Aspfsny`, `Aspmpay`, `Aspmpgy`, `Aspmply`, `Aspmpny`, `Aspmsayn`, `Aspmsayy`, `Aspmsdn`, `Aspmsdy`, `Aspmsgn`, `Aspmsgy`, `Aspmsiy`, `Aspmsln`, `Aspmsly`, `Aspmsnn`, `Aspnpay`, `Aspnpgy`, `Aspnpny`, `Aspnsay`, `Aspnsgn`, `Aspnsgy`, `Aspnsln`, `Aspnsly`, `Aspnsny`, `Cc`, `Cs`, `I`, `Mdc`, `Mdm`, `Mdo`, `Mds`, `Mlc`, `Mlc--g`, `Mlc--i`, `Mlc--l`, `Mlcf-a`, `Mlcf-d`, `Mlcf-g`, `Mlcf-n`, `Mlcfsa`, `Mlcfsd`, `Mlcfsg`, `Mlcfsi`, `Mlcfsl`, `Mlcfsn`, `Mlcm-a`, `Mlcm-g`, `Mlcm-l`, `Mlcm-n`, `Mlcmpn`, `Mlcmsan`, `Mlcmsay`, `Mlcmsg`, `Mlcmsi`, `Mlcmsl`, `Mlcmsn`, `Mlcn-n`, `Mlcnsa`, `Mlcnsg`, `Mlcnsn`, `Mlofpa`, `Mlofpd`, `Mlofpg`, `Mlofpi`, `Mlofpl`, `Mlofpn`, `Mlofsa`, `Mlofsd`, `Mlofsg`, `Mlofsi`, `Mlofsl`, `Mlofsn`, `Mlompa`, `Mlompd`, `Mlompg`, `Mlompi`, `Mlompl`, `Mlompn`, `Mlomsan`, `Mlomsay`, `Mlomsd`, `Mlomsg`, `Mlomsi`, `Mlomsl`, `Mlomsn`, `Mlonpa`, `Mlonpg`, `Mlonpl`, `Mlonpn`, `Mlonsa`, `Mlonsd`, `Mlonsg`, `Mlonsi`, `Mlonsl`, `Mlonsn`, `Mls`, `Mlsf-a`, `Mlsf-g`, `Mlsf-i`, `Mlsf-l`, `Mlsf-n`, `Mlsm-a`, `Mlsm-g`, `Mlsm-l`, `Mlsm-n`, `Mlsmpn`, `Mlsn-n`, `Mrc`, `Mro`, `Ncfpa`, `Ncfpd`, `Ncfpg`, `Ncfpi`, `Ncfpl`, `Ncfpn`, `Ncfpv`, `Ncfsa`, `Ncfsd`, `Ncfsg`, `Ncfsi`, `Ncfsl`, `Ncfsn`, `Ncfsv`, `Ncmpa`, `Ncmpd`, `Ncmpg`, `Ncmpi`, `Ncmpl`, `Ncmpn`, `Ncmpv`, `Ncmsan`, `Ncmsay`, `Ncmsd`, `Ncmsg`, `Ncmsi`, `Ncmsl`, `Ncmsn`, `Ncmsv`, `Ncnpa`, `Ncnpd`, `Ncnpg`, `Ncnpi`, `Ncnpl`, `Ncnpn`, `Ncnsa`, `Ncnsd`, `Ncnsg`, `Ncnsi`, `Ncnsl`, `Ncnsn`, `Ncnsv`, `Npfpa`, `Npfpg`, `Npfpl`, `Npfpn`, `Npfsa`, `Npfsd`, `Npfsg`, `Npfsi`, `Npfsl`, `Npfsn`, `Npmpa`, `Npmpd`, `Npmpg`, `Npmpi`, `Npmpl`, `Npmpn`, `Npmsan`, `Npmsay`, `Npmsd`, `Npmsg`, `Npmsi`, `Npmsl`, `Npmsn`, `Npmsv`, `Npnpg`, `Npnpn`, `Npnsa`, `Npnsd`, `Npnsg`, `Npnsi`, `Npnsl`, `Npnsn`, `Pd-fpa`, `Pd-fpd`, `Pd-fpg`, `Pd-fpi`, `Pd-fpl`, `Pd-fpn`, `Pd-fsa`, `Pd-fsd`, `Pd-fsg`, `Pd-fsi`, `Pd-fsl`, `Pd-fsn`, `Pd-mpa`, `Pd-mpd`, `Pd-mpg`, `Pd-mpi`, `Pd-mpl`, `Pd-mpn`, `Pd-msan`, `Pd-msay`, `Pd-msd`, `Pd-msg`, `Pd-msi`, `Pd-msl`, `Pd-msn`, `Pd-npa`, `Pd-npg`, `Pd-npi`, `Pd-npn`, `Pd-nsa`, `Pd-nsd`, `Pd-nsg`, `Pd-nsi`, `Pd-nsl`, `Pd-nsn`, `Pi-fpa`, `Pi-fpd`, `Pi-fpg`, `Pi-fpi`, `Pi-fpl`, `Pi-fpn`, `Pi-fsa`, `Pi-fsd`, `Pi-fsg`, `Pi-fsi`, `Pi-fsl`, `Pi-fsn`, `Pi-mpa`, `Pi-mpd`, `Pi-mpg`, `Pi-mpi`, `Pi-mpl`, `Pi-mpn`, `Pi-msan`, `Pi-msay`, `Pi-msd`, `Pi-msg`, `Pi-msi`, `Pi-msl`, `Pi-msn`, `Pi-npa`, `Pi-npd`, `Pi-npg`, `Pi-npi`, `Pi-npl`, `Pi-npn`, `Pi-nsa`, `Pi-nsd`, `Pi-nsg`, `Pi-nsi`, `Pi-nsl`, `Pi-nsn`, `Pi3m-a`, `Pi3m-d`, `Pi3m-g`, `Pi3m-i`, `Pi3m-n`, `Pi3n-a`, `Pi3n-d`, `Pi3n-g`, `Pi3n-i`, `Pi3n-l`, `Pi3n-n`, `Pp1-pa`, `Pp1-pd`, `Pp1-pg`, `Pp1-pi`, `Pp1-pl`, `Pp1-pn`, `Pp1-sa`, `Pp1-sd`, `Pp1-sg`, `Pp1-si`, `Pp1-sl`, `Pp1-sn`, `Pp2-pa`, `Pp2-pd`, `Pp2-pl`, `Pp2-pn`, `Pp2-sa`, `Pp2-sd`, `Pp2-sg`, `Pp2-sl`, `Pp2-sn`, `Pp3-pa`, `Pp3-pd`, `Pp3-pg`, `Pp3-pi`, `Pp3-pl`, `Pp3fpn`, `Pp3fsa`, `Pp3fsd`, `Pp3fsg`, `Pp3fsi`, `Pp3fsl`, `Pp3fsn`, `Pp3mpn`, `Pp3msa`, `Pp3msd`, `Pp3msg`, `Pp3msi`, `Pp3msl`, `Pp3msn`, `Pp3npn`, `Pp3nsa`, `Pp3nsi`, `Pp3nsn`, `Pq-fpa`, `Pq-fpn`, `Pq-fsa`, `Pq-fsi`, `Pq-fsl`, `Pq-fsn`, `Pq-mpn`, `Pq-msn`, `Pq-nsn`, `Pq3m-d`, `Pq3m-n`, `Pq3n-a`, `Pq3n-l`, `Pq3n-n`, `Ps1fpa`, `Ps1fpg`, `Ps1fpl`, `Ps1fpn`, `Ps1fsa`, `Ps1fsd`, `Ps1fsg`, `Ps1fsi`, `Ps1fsl`, `Ps1fsn`, _(truncated: full list in pipeline meta)_ | | **`morphologizer`** | `Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Loc\|POS=ADP`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Ins\|POS=ADP`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Degree=Pos\|POS=ADV`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=NOUN`, `POS=PUNCT`, `POS=PART`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=SCONJ`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=CCONJ`, `Case=Gen\|POS=ADP`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `POS=VERB\|VerbForm=Inf`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `POS=PART\|Polarity=Neg`, `Case=Acc\|Gender=Neut\|POS=PRON\|PronType=Neg`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Degree=Pos\|POS=ADV\|PronType=Dem`, `Degree=Cmp\|POS=ADV`, `Case=Acc\|POS=ADP`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `NumType=Ord\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Gender=Fem\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|POS=PRON\|PronType=Int,Rel`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Gender=Fem\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `NumType=Card\|POS=NUM`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Degree=Pos\|POS=ADV\|PronType=Int,Rel`, `Gender=Neut\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Gender=Masc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Gen\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Loc\|Gender=Neut\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `POS=X`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Definite=Def\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Gen\|Gender=Neut\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Anim\|Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `POS=AUX\|VerbForm=Inf`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Gender=Fem\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Degree=Pos\|POS=ADV\|PronType=Ind`, `Animacy=Inan\|Case=Acc\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Degree=Pos\|POS=ADV\|PronType=Neg`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Masc\|POS=PRON\|PronType=Neg`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `POS=NOUN`, `Case=Voc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Acc\|Gender=Masc\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Loc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Loc\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=NOUN`, `POS=SPACE`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|POS=PRON\|PronType=Ind`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Animacy=Inan\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Gender=Masc\|POS=PRON\|PronType=Neg`, `Case=Ins\|Gender=Neut\|POS=PRON\|PronType=Int,Rel`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|POS=ADP`, `Degree=Sup\|POS=ADV`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `POS=ADV\|Tense=Pres\|VerbForm=Conv`, `Case=Ins\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Neut\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Fem\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `NumType=Mult\|POS=NUM`, `Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Fem\|NumType=Mult\|POS=NUM`, `Case=Acc\|Gender=Neut\|POS=PRON\|PronType=Int,Rel`, `Animacy=Inan\|Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|NumType=Mult\|POS=NUM`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Loc\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Dat\|Gender=Masc\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Loc\|Gender=Neut\|POS=PRON\|PronType=Int,Rel`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `POS=ADV\|Tense=Past\|VerbForm=Conv`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|POS=PRON\|PronType=Int,Rel`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Definite=Def\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Ins\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Degree=Pos\|POS=ADV\|PronType=Tot`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Gender=Masc\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Ins\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Dat\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Ins\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|POS=PRON\|PronType=Neg`, `Case=Gen\|Gender=Masc\|NumType=Mult\|POS=NUM`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Animacy=Inan\|Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Gender=Neut\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Ins\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Neut\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|POS=PRON\|PronType=Ind`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Ins\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Masc\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `NumType=Mult\|POS=SYM`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Masc\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Loc\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Nom\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Nom\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=2\|Tense=Past\|VerbForm=Fin`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Neg`, `Case=Loc\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=SYM`, `Case=Ins\|Definite=Def\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Gen\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Anim\|Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Gender=Masc\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Ins\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Acc\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Neut\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|NumType=Card\|Number=Plur\|POS=NUM`, `Animacy=Anim\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Anim\|Case=Acc\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Ind\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Nom\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, _(truncated: full list in pipeline meta)_ | | **`parser`** | `ROOT`, `acl`, `advcl`, `advmod`, `advmod:emph`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `ccomp`, `compound`, `conj`, `cop`, `csubj`, `csubj:pass`, `dep`, `det`, `discourse`, `expl:pv`, `fixed`, `flat`, `flat:foreign`, `goeswith`, `iobj`, `mark`, `nmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `orphan`, `parataxis`, `punct`, `xcomp` | | **`ner`** | `DERIV_PER`, `LOC`, `MISC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.89 | | `TOKEN_P` | 97.28 | | `TOKEN_R` | 98.71 | | `TOKEN_F` | 97.99 | | `TAG_ACC` | 92.17 | | `POS_ACC` | 97.59 | | `MORPH_ACC` | 92.68 | | `MORPH_MICRO_P` | 96.20 | | `MORPH_MICRO_R` | 95.88 | | `MORPH_MICRO_F` | 96.04 | | `SENTS_P` | 95.59 | | `SENTS_R` | 93.53 | | `SENTS_F` | 94.55 | | `DEP_UAS` | 86.62 | | `DEP_LAS` | 80.16 | | `LEMMA_ACC` | 92.88 | | `ENTS_P` | 83.09 | | `ENTS_R` | 82.95 | | `ENTS_F` | 83.02 |
spacy/hr_core_news_md
spacy
2023-10-10T06:47:04Z
0
0
spacy
[ "spacy", "token-classification", "hr", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-07-20T08:07:10Z
--- tags: - spacy - token-classification language: - hr license: cc-by-sa-4.0 model-index: - name: hr_core_news_md results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8244343891 - name: NER Recall type: recall value: 0.8133928571 - name: NER F Score type: f_score value: 0.8188764045 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9168748959 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9732718382 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9231452688 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9281478417 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8645157205 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.800506249 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9425287356 --- ### Details: https://spacy.io/models/hr#hr_core_news_md Croatian pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner. | Feature | Description | | --- | --- | | **Name** | `hr_core_news_md` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | floret (50000, 300) | | **Sources** | [Training corpus hr500k 1.0](http://hdl.handle.net/11356/1183) (Ljubešić, Nikola ; Agić, Željko ; Klubička, Filip ; Batanović, Vuk and Erjavec, Tomaž)<br />[Explosion Vectors (OSCAR 2109 + Wikipedia + OpenSubtitles + WMT News Crawl)](https://github.com/explosion/spacy-vectors-builder) (Explosion) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (1518 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `Agcfpay`, `Agcfpdy`, `Agcfpgy`, `Agcfpiy`, `Agcfply`, `Agcfpny`, `Agcfsay`, `Agcfsdy`, `Agcfsgy`, `Agcfsiy`, `Agcfsly`, `Agcfsny`, `Agcmpay`, `Agcmpgy`, `Agcmpiy`, `Agcmpny`, `Agcmsany`, `Agcmsay`, `Agcmsayn`, `Agcmsdy`, `Agcmsgy`, `Agcmsiy`, `Agcmsly`, `Agcmsny`, `Agcnpay`, `Agcnpdy`, `Agcnpgy`, `Agcnpny`, `Agcnsay`, `Agcnsdy`, `Agcnsgy`, `Agcnsiy`, `Agcnsly`, `Agcnsny`, `Agpfpay`, `Agpfpdy`, `Agpfpgy`, `Agpfpiy`, `Agpfply`, `Agpfpny`, `Agpfsay`, `Agpfsdy`, `Agpfsgy`, `Agpfsin`, `Agpfsiy`, `Agpfsly`, `Agpfsny`, `Agpfsvy`, `Agpmpay`, `Agpmpdy`, `Agpmpgy`, `Agpmpiy`, `Agpmply`, `Agpmpny`, `Agpmsan`, `Agpmsann`, `Agpmsany`, `Agpmsay`, `Agpmsayn`, `Agpmsayy`, `Agpmsdy`, `Agpmsgn`, `Agpmsgy`, `Agpmsiy`, `Agpmsln`, `Agpmsly`, `Agpmsnn`, `Agpmsny`, `Agpmsvy`, `Agpnpay`, `Agpnpdy`, `Agpnpgy`, `Agpnpiy`, `Agpnply`, `Agpnpny`, `Agpnsay`, `Agpnsdy`, `Agpnsgn`, `Agpnsgy`, `Agpnsiy`, `Agpnsln`, `Agpnsly`, `Agpnsny`, `Agsfpay`, `Agsfpdy`, `Agsfpgy`, `Agsfpiy`, `Agsfply`, `Agsfpny`, `Agsfsay`, `Agsfsdy`, `Agsfsgy`, `Agsfsiy`, `Agsfsly`, `Agsfsny`, `Agsmpay`, `Agsmpdy`, `Agsmpgy`, `Agsmpiy`, `Agsmply`, `Agsmpny`, `Agsmsany`, `Agsmsayn`, `Agsmsayy`, `Agsmsdy`, `Agsmsgy`, `Agsmsiy`, `Agsmsly`, `Agsmsny`, `Agsnpay`, `Agsnpgy`, `Agsnply`, `Agsnpny`, `Agsnsay`, `Agsnsdy`, `Agsnsgy`, `Agsnsiy`, `Agsnsly`, `Agsnsny`, `Appfpay`, `Appfpdy`, `Appfpgy`, `Appfpiy`, `Appfply`, `Appfpny`, `Appfsay`, `Appfsgy`, `Appfsiy`, `Appfsly`, `Appfsny`, `Appmpay`, `Appmpdy`, `Appmpgy`, `Appmpiy`, `Appmply`, `Appmpny`, `Appmsann`, `Appmsany`, `Appmsayn`, `Appmsayy`, `Appmsdy`, `Appmsgn`, `Appmsgy`, `Appmsiy`, `Appmsly`, `Appmsnn`, `Appmsny`, `Appnpay`, `Appnpdy`, `Appnpgy`, `Appnpiy`, `Appnply`, `Appnpny`, `Appnsay`, `Appnsgy`, `Appnsly`, `Appnsny`, `Aspfpay`, `Aspfpgy`, `Aspfpiy`, `Aspfply`, `Aspfpny`, `Aspfsay`, `Aspfsdy`, `Aspfsgy`, `Aspfsly`, `Aspfsny`, `Aspmpay`, `Aspmpgy`, `Aspmply`, `Aspmpny`, `Aspmsayn`, `Aspmsayy`, `Aspmsdn`, `Aspmsdy`, `Aspmsgn`, `Aspmsgy`, `Aspmsiy`, `Aspmsln`, `Aspmsly`, `Aspmsnn`, `Aspnpay`, `Aspnpgy`, `Aspnpny`, `Aspnsay`, `Aspnsgn`, `Aspnsgy`, `Aspnsln`, `Aspnsly`, `Aspnsny`, `Cc`, `Cs`, `I`, `Mdc`, `Mdm`, `Mdo`, `Mds`, `Mlc`, `Mlc--g`, `Mlc--i`, `Mlc--l`, `Mlcf-a`, `Mlcf-d`, `Mlcf-g`, `Mlcf-n`, `Mlcfsa`, `Mlcfsd`, `Mlcfsg`, `Mlcfsi`, `Mlcfsl`, `Mlcfsn`, `Mlcm-a`, `Mlcm-g`, `Mlcm-l`, `Mlcm-n`, `Mlcmpn`, `Mlcmsan`, `Mlcmsay`, `Mlcmsg`, `Mlcmsi`, `Mlcmsl`, `Mlcmsn`, `Mlcn-n`, `Mlcnsa`, `Mlcnsg`, `Mlcnsn`, `Mlofpa`, `Mlofpd`, `Mlofpg`, `Mlofpi`, `Mlofpl`, `Mlofpn`, `Mlofsa`, `Mlofsd`, `Mlofsg`, `Mlofsi`, `Mlofsl`, `Mlofsn`, `Mlompa`, `Mlompd`, `Mlompg`, `Mlompi`, `Mlompl`, `Mlompn`, `Mlomsan`, `Mlomsay`, `Mlomsd`, `Mlomsg`, `Mlomsi`, `Mlomsl`, `Mlomsn`, `Mlonpa`, `Mlonpg`, `Mlonpl`, `Mlonpn`, `Mlonsa`, `Mlonsd`, `Mlonsg`, `Mlonsi`, `Mlonsl`, `Mlonsn`, `Mls`, `Mlsf-a`, `Mlsf-g`, `Mlsf-i`, `Mlsf-l`, `Mlsf-n`, `Mlsm-a`, `Mlsm-g`, `Mlsm-l`, `Mlsm-n`, `Mlsmpn`, `Mlsn-n`, `Mrc`, `Mro`, `Ncfpa`, `Ncfpd`, `Ncfpg`, `Ncfpi`, `Ncfpl`, `Ncfpn`, `Ncfpv`, `Ncfsa`, `Ncfsd`, `Ncfsg`, `Ncfsi`, `Ncfsl`, `Ncfsn`, `Ncfsv`, `Ncmpa`, `Ncmpd`, `Ncmpg`, `Ncmpi`, `Ncmpl`, `Ncmpn`, `Ncmpv`, `Ncmsan`, `Ncmsay`, `Ncmsd`, `Ncmsg`, `Ncmsi`, `Ncmsl`, `Ncmsn`, `Ncmsv`, `Ncnpa`, `Ncnpd`, `Ncnpg`, `Ncnpi`, `Ncnpl`, `Ncnpn`, `Ncnsa`, `Ncnsd`, `Ncnsg`, `Ncnsi`, `Ncnsl`, `Ncnsn`, `Ncnsv`, `Npfpa`, `Npfpg`, `Npfpl`, `Npfpn`, `Npfsa`, `Npfsd`, `Npfsg`, `Npfsi`, `Npfsl`, `Npfsn`, `Npmpa`, `Npmpd`, `Npmpg`, `Npmpi`, `Npmpl`, `Npmpn`, `Npmsan`, `Npmsay`, `Npmsd`, `Npmsg`, `Npmsi`, `Npmsl`, `Npmsn`, `Npmsv`, `Npnpg`, `Npnpn`, `Npnsa`, `Npnsd`, `Npnsg`, `Npnsi`, `Npnsl`, `Npnsn`, `Pd-fpa`, `Pd-fpd`, `Pd-fpg`, `Pd-fpi`, `Pd-fpl`, `Pd-fpn`, `Pd-fsa`, `Pd-fsd`, `Pd-fsg`, `Pd-fsi`, `Pd-fsl`, `Pd-fsn`, `Pd-mpa`, `Pd-mpd`, `Pd-mpg`, `Pd-mpi`, `Pd-mpl`, `Pd-mpn`, `Pd-msan`, `Pd-msay`, `Pd-msd`, `Pd-msg`, `Pd-msi`, `Pd-msl`, `Pd-msn`, `Pd-npa`, `Pd-npg`, `Pd-npi`, `Pd-npn`, `Pd-nsa`, `Pd-nsd`, `Pd-nsg`, `Pd-nsi`, `Pd-nsl`, `Pd-nsn`, `Pi-fpa`, `Pi-fpd`, `Pi-fpg`, `Pi-fpi`, `Pi-fpl`, `Pi-fpn`, `Pi-fsa`, `Pi-fsd`, `Pi-fsg`, `Pi-fsi`, `Pi-fsl`, `Pi-fsn`, `Pi-mpa`, `Pi-mpd`, `Pi-mpg`, `Pi-mpi`, `Pi-mpl`, `Pi-mpn`, `Pi-msan`, `Pi-msay`, `Pi-msd`, `Pi-msg`, `Pi-msi`, `Pi-msl`, `Pi-msn`, `Pi-npa`, `Pi-npd`, `Pi-npg`, `Pi-npi`, `Pi-npl`, `Pi-npn`, `Pi-nsa`, `Pi-nsd`, `Pi-nsg`, `Pi-nsi`, `Pi-nsl`, `Pi-nsn`, `Pi3m-a`, `Pi3m-d`, `Pi3m-g`, `Pi3m-i`, `Pi3m-n`, `Pi3n-a`, `Pi3n-d`, `Pi3n-g`, `Pi3n-i`, `Pi3n-l`, `Pi3n-n`, `Pp1-pa`, `Pp1-pd`, `Pp1-pg`, `Pp1-pi`, `Pp1-pl`, `Pp1-pn`, `Pp1-sa`, `Pp1-sd`, `Pp1-sg`, `Pp1-si`, `Pp1-sl`, `Pp1-sn`, `Pp2-pa`, `Pp2-pd`, `Pp2-pl`, `Pp2-pn`, `Pp2-sa`, `Pp2-sd`, `Pp2-sg`, `Pp2-sl`, `Pp2-sn`, `Pp3-pa`, `Pp3-pd`, `Pp3-pg`, `Pp3-pi`, `Pp3-pl`, `Pp3fpn`, `Pp3fsa`, `Pp3fsd`, `Pp3fsg`, `Pp3fsi`, `Pp3fsl`, `Pp3fsn`, `Pp3mpn`, `Pp3msa`, `Pp3msd`, `Pp3msg`, `Pp3msi`, `Pp3msl`, `Pp3msn`, `Pp3npn`, `Pp3nsa`, `Pp3nsi`, `Pp3nsn`, `Pq-fpa`, `Pq-fpn`, `Pq-fsa`, `Pq-fsi`, `Pq-fsl`, `Pq-fsn`, `Pq-mpn`, `Pq-msn`, `Pq-nsn`, `Pq3m-d`, `Pq3m-n`, `Pq3n-a`, `Pq3n-l`, `Pq3n-n`, `Ps1fpa`, `Ps1fpg`, `Ps1fpl`, `Ps1fpn`, `Ps1fsa`, `Ps1fsd`, `Ps1fsg`, `Ps1fsi`, `Ps1fsl`, `Ps1fsn`, _(truncated: full list in pipeline meta)_ | | **`morphologizer`** | `Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Loc\|POS=ADP`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Ins\|POS=ADP`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Degree=Pos\|POS=ADV`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=NOUN`, `POS=PUNCT`, `POS=PART`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=SCONJ`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=CCONJ`, `Case=Gen\|POS=ADP`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `POS=VERB\|VerbForm=Inf`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `POS=PART\|Polarity=Neg`, `Case=Acc\|Gender=Neut\|POS=PRON\|PronType=Neg`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Degree=Pos\|POS=ADV\|PronType=Dem`, `Degree=Cmp\|POS=ADV`, `Case=Acc\|POS=ADP`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `NumType=Ord\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Gender=Fem\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|POS=PRON\|PronType=Int,Rel`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Gender=Fem\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `NumType=Card\|POS=NUM`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Degree=Pos\|POS=ADV\|PronType=Int,Rel`, `Gender=Neut\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Gender=Masc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Gen\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Loc\|Gender=Neut\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `POS=X`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Definite=Def\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Gen\|Gender=Neut\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Anim\|Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `POS=AUX\|VerbForm=Inf`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Gender=Fem\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Degree=Pos\|POS=ADV\|PronType=Ind`, `Animacy=Inan\|Case=Acc\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Degree=Pos\|POS=ADV\|PronType=Neg`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Masc\|POS=PRON\|PronType=Neg`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `POS=NOUN`, `Case=Voc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Acc\|Gender=Masc\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Loc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Loc\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=NOUN`, `POS=SPACE`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|POS=PRON\|PronType=Ind`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Animacy=Inan\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Gender=Masc\|POS=PRON\|PronType=Neg`, `Case=Ins\|Gender=Neut\|POS=PRON\|PronType=Int,Rel`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|POS=ADP`, `Degree=Sup\|POS=ADV`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `POS=ADV\|Tense=Pres\|VerbForm=Conv`, `Case=Ins\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Neut\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Fem\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `NumType=Mult\|POS=NUM`, `Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Fem\|NumType=Mult\|POS=NUM`, `Case=Acc\|Gender=Neut\|POS=PRON\|PronType=Int,Rel`, `Animacy=Inan\|Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|NumType=Mult\|POS=NUM`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Loc\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Dat\|Gender=Masc\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Loc\|Gender=Neut\|POS=PRON\|PronType=Int,Rel`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `POS=ADV\|Tense=Past\|VerbForm=Conv`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|POS=PRON\|PronType=Int,Rel`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Definite=Def\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Ins\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Degree=Pos\|POS=ADV\|PronType=Tot`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Gender=Masc\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Ins\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Dat\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Ins\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|POS=PRON\|PronType=Neg`, `Case=Gen\|Gender=Masc\|NumType=Mult\|POS=NUM`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Animacy=Inan\|Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Gender=Neut\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Ins\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Neut\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|POS=PRON\|PronType=Ind`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Ins\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Masc\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `NumType=Mult\|POS=SYM`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Masc\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Loc\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Nom\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Nom\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=2\|Tense=Past\|VerbForm=Fin`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Neg`, `Case=Loc\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=SYM`, `Case=Ins\|Definite=Def\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Gen\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Anim\|Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Gender=Masc\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Ins\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Acc\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Neut\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|NumType=Card\|Number=Plur\|POS=NUM`, `Animacy=Anim\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Anim\|Case=Acc\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Ind\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Nom\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, _(truncated: full list in pipeline meta)_ | | **`parser`** | `ROOT`, `acl`, `advcl`, `advmod`, `advmod:emph`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `ccomp`, `compound`, `conj`, `cop`, `csubj`, `csubj:pass`, `dep`, `det`, `discourse`, `expl:pv`, `fixed`, `flat`, `flat:foreign`, `goeswith`, `iobj`, `mark`, `nmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `orphan`, `parataxis`, `punct`, `xcomp` | | **`ner`** | `DERIV_PER`, `LOC`, `MISC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.89 | | `TOKEN_P` | 97.28 | | `TOKEN_R` | 98.71 | | `TOKEN_F` | 97.99 | | `TAG_ACC` | 91.69 | | `POS_ACC` | 97.33 | | `MORPH_ACC` | 92.31 | | `MORPH_MICRO_P` | 95.98 | | `MORPH_MICRO_R` | 95.56 | | `MORPH_MICRO_F` | 95.77 | | `SENTS_P` | 95.12 | | `SENTS_R` | 93.41 | | `SENTS_F` | 94.25 | | `DEP_UAS` | 86.45 | | `DEP_LAS` | 80.05 | | `LEMMA_ACC` | 92.81 | | `ENTS_P` | 82.44 | | `ENTS_R` | 81.34 | | `ENTS_F` | 81.89 |
spacy/hr_core_news_sm
spacy
2023-10-10T06:46:56Z
5
0
spacy
[ "spacy", "token-classification", "hr", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-07-20T08:06:57Z
--- tags: - spacy - token-classification language: - hr license: cc-by-sa-4.0 model-index: - name: hr_core_news_sm results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7738095238 - name: NER Recall type: recall value: 0.7544642857 - name: NER F Score type: f_score value: 0.7640144665 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9002581684 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9673834528 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9062135599 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9194318025 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8446878561 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.776466867 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9483793517 --- ### Details: https://spacy.io/models/hr#hr_core_news_sm Croatian pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner. | Feature | Description | | --- | --- | | **Name** | `hr_core_news_sm` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | | **Sources** | [Training corpus hr500k 1.0](http://hdl.handle.net/11356/1183) (Ljubešić, Nikola ; Agić, Željko ; Klubička, Filip ; Batanović, Vuk and Erjavec, Tomaž) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (1518 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `Agcfpay`, `Agcfpdy`, `Agcfpgy`, `Agcfpiy`, `Agcfply`, `Agcfpny`, `Agcfsay`, `Agcfsdy`, `Agcfsgy`, `Agcfsiy`, `Agcfsly`, `Agcfsny`, `Agcmpay`, `Agcmpgy`, `Agcmpiy`, `Agcmpny`, `Agcmsany`, `Agcmsay`, `Agcmsayn`, `Agcmsdy`, `Agcmsgy`, `Agcmsiy`, `Agcmsly`, `Agcmsny`, `Agcnpay`, `Agcnpdy`, `Agcnpgy`, `Agcnpny`, `Agcnsay`, `Agcnsdy`, `Agcnsgy`, `Agcnsiy`, `Agcnsly`, `Agcnsny`, `Agpfpay`, `Agpfpdy`, `Agpfpgy`, `Agpfpiy`, `Agpfply`, `Agpfpny`, `Agpfsay`, `Agpfsdy`, `Agpfsgy`, `Agpfsin`, `Agpfsiy`, `Agpfsly`, `Agpfsny`, `Agpfsvy`, `Agpmpay`, `Agpmpdy`, `Agpmpgy`, `Agpmpiy`, `Agpmply`, `Agpmpny`, `Agpmsan`, `Agpmsann`, `Agpmsany`, `Agpmsay`, `Agpmsayn`, `Agpmsayy`, `Agpmsdy`, `Agpmsgn`, `Agpmsgy`, `Agpmsiy`, `Agpmsln`, `Agpmsly`, `Agpmsnn`, `Agpmsny`, `Agpmsvy`, `Agpnpay`, `Agpnpdy`, `Agpnpgy`, `Agpnpiy`, `Agpnply`, `Agpnpny`, `Agpnsay`, `Agpnsdy`, `Agpnsgn`, `Agpnsgy`, `Agpnsiy`, `Agpnsln`, `Agpnsly`, `Agpnsny`, `Agsfpay`, `Agsfpdy`, `Agsfpgy`, `Agsfpiy`, `Agsfply`, `Agsfpny`, `Agsfsay`, `Agsfsdy`, `Agsfsgy`, `Agsfsiy`, `Agsfsly`, `Agsfsny`, `Agsmpay`, `Agsmpdy`, `Agsmpgy`, `Agsmpiy`, `Agsmply`, `Agsmpny`, `Agsmsany`, `Agsmsayn`, `Agsmsayy`, `Agsmsdy`, `Agsmsgy`, `Agsmsiy`, `Agsmsly`, `Agsmsny`, `Agsnpay`, `Agsnpgy`, `Agsnply`, `Agsnpny`, `Agsnsay`, `Agsnsdy`, `Agsnsgy`, `Agsnsiy`, `Agsnsly`, `Agsnsny`, `Appfpay`, `Appfpdy`, `Appfpgy`, `Appfpiy`, `Appfply`, `Appfpny`, `Appfsay`, `Appfsgy`, `Appfsiy`, `Appfsly`, `Appfsny`, `Appmpay`, `Appmpdy`, `Appmpgy`, `Appmpiy`, `Appmply`, `Appmpny`, `Appmsann`, `Appmsany`, `Appmsayn`, `Appmsayy`, `Appmsdy`, `Appmsgn`, `Appmsgy`, `Appmsiy`, `Appmsly`, `Appmsnn`, `Appmsny`, `Appnpay`, `Appnpdy`, `Appnpgy`, `Appnpiy`, `Appnply`, `Appnpny`, `Appnsay`, `Appnsgy`, `Appnsly`, `Appnsny`, `Aspfpay`, `Aspfpgy`, `Aspfpiy`, `Aspfply`, `Aspfpny`, `Aspfsay`, `Aspfsdy`, `Aspfsgy`, `Aspfsly`, `Aspfsny`, `Aspmpay`, `Aspmpgy`, `Aspmply`, `Aspmpny`, `Aspmsayn`, `Aspmsayy`, `Aspmsdn`, `Aspmsdy`, `Aspmsgn`, `Aspmsgy`, `Aspmsiy`, `Aspmsln`, `Aspmsly`, `Aspmsnn`, `Aspnpay`, `Aspnpgy`, `Aspnpny`, `Aspnsay`, `Aspnsgn`, `Aspnsgy`, `Aspnsln`, `Aspnsly`, `Aspnsny`, `Cc`, `Cs`, `I`, `Mdc`, `Mdm`, `Mdo`, `Mds`, `Mlc`, `Mlc--g`, `Mlc--i`, `Mlc--l`, `Mlcf-a`, `Mlcf-d`, `Mlcf-g`, `Mlcf-n`, `Mlcfsa`, `Mlcfsd`, `Mlcfsg`, `Mlcfsi`, `Mlcfsl`, `Mlcfsn`, `Mlcm-a`, `Mlcm-g`, `Mlcm-l`, `Mlcm-n`, `Mlcmpn`, `Mlcmsan`, `Mlcmsay`, `Mlcmsg`, `Mlcmsi`, `Mlcmsl`, `Mlcmsn`, `Mlcn-n`, `Mlcnsa`, `Mlcnsg`, `Mlcnsn`, `Mlofpa`, `Mlofpd`, `Mlofpg`, `Mlofpi`, `Mlofpl`, `Mlofpn`, `Mlofsa`, `Mlofsd`, `Mlofsg`, `Mlofsi`, `Mlofsl`, `Mlofsn`, `Mlompa`, `Mlompd`, `Mlompg`, `Mlompi`, `Mlompl`, `Mlompn`, `Mlomsan`, `Mlomsay`, `Mlomsd`, `Mlomsg`, `Mlomsi`, `Mlomsl`, `Mlomsn`, `Mlonpa`, `Mlonpg`, `Mlonpl`, `Mlonpn`, `Mlonsa`, `Mlonsd`, `Mlonsg`, `Mlonsi`, `Mlonsl`, `Mlonsn`, `Mls`, `Mlsf-a`, `Mlsf-g`, `Mlsf-i`, `Mlsf-l`, `Mlsf-n`, `Mlsm-a`, `Mlsm-g`, `Mlsm-l`, `Mlsm-n`, `Mlsmpn`, `Mlsn-n`, `Mrc`, `Mro`, `Ncfpa`, `Ncfpd`, `Ncfpg`, `Ncfpi`, `Ncfpl`, `Ncfpn`, `Ncfpv`, `Ncfsa`, `Ncfsd`, `Ncfsg`, `Ncfsi`, `Ncfsl`, `Ncfsn`, `Ncfsv`, `Ncmpa`, `Ncmpd`, `Ncmpg`, `Ncmpi`, `Ncmpl`, `Ncmpn`, `Ncmpv`, `Ncmsan`, `Ncmsay`, `Ncmsd`, `Ncmsg`, `Ncmsi`, `Ncmsl`, `Ncmsn`, `Ncmsv`, `Ncnpa`, `Ncnpd`, `Ncnpg`, `Ncnpi`, `Ncnpl`, `Ncnpn`, `Ncnsa`, `Ncnsd`, `Ncnsg`, `Ncnsi`, `Ncnsl`, `Ncnsn`, `Ncnsv`, `Npfpa`, `Npfpg`, `Npfpl`, `Npfpn`, `Npfsa`, `Npfsd`, `Npfsg`, `Npfsi`, `Npfsl`, `Npfsn`, `Npmpa`, `Npmpd`, `Npmpg`, `Npmpi`, `Npmpl`, `Npmpn`, `Npmsan`, `Npmsay`, `Npmsd`, `Npmsg`, `Npmsi`, `Npmsl`, `Npmsn`, `Npmsv`, `Npnpg`, `Npnpn`, `Npnsa`, `Npnsd`, `Npnsg`, `Npnsi`, `Npnsl`, `Npnsn`, `Pd-fpa`, `Pd-fpd`, `Pd-fpg`, `Pd-fpi`, `Pd-fpl`, `Pd-fpn`, `Pd-fsa`, `Pd-fsd`, `Pd-fsg`, `Pd-fsi`, `Pd-fsl`, `Pd-fsn`, `Pd-mpa`, `Pd-mpd`, `Pd-mpg`, `Pd-mpi`, `Pd-mpl`, `Pd-mpn`, `Pd-msan`, `Pd-msay`, `Pd-msd`, `Pd-msg`, `Pd-msi`, `Pd-msl`, `Pd-msn`, `Pd-npa`, `Pd-npg`, `Pd-npi`, `Pd-npn`, `Pd-nsa`, `Pd-nsd`, `Pd-nsg`, `Pd-nsi`, `Pd-nsl`, `Pd-nsn`, `Pi-fpa`, `Pi-fpd`, `Pi-fpg`, `Pi-fpi`, `Pi-fpl`, `Pi-fpn`, `Pi-fsa`, `Pi-fsd`, `Pi-fsg`, `Pi-fsi`, `Pi-fsl`, `Pi-fsn`, `Pi-mpa`, `Pi-mpd`, `Pi-mpg`, `Pi-mpi`, `Pi-mpl`, `Pi-mpn`, `Pi-msan`, `Pi-msay`, `Pi-msd`, `Pi-msg`, `Pi-msi`, `Pi-msl`, `Pi-msn`, `Pi-npa`, `Pi-npd`, `Pi-npg`, `Pi-npi`, `Pi-npl`, `Pi-npn`, `Pi-nsa`, `Pi-nsd`, `Pi-nsg`, `Pi-nsi`, `Pi-nsl`, `Pi-nsn`, `Pi3m-a`, `Pi3m-d`, `Pi3m-g`, `Pi3m-i`, `Pi3m-n`, `Pi3n-a`, `Pi3n-d`, `Pi3n-g`, `Pi3n-i`, `Pi3n-l`, `Pi3n-n`, `Pp1-pa`, `Pp1-pd`, `Pp1-pg`, `Pp1-pi`, `Pp1-pl`, `Pp1-pn`, `Pp1-sa`, `Pp1-sd`, `Pp1-sg`, `Pp1-si`, `Pp1-sl`, `Pp1-sn`, `Pp2-pa`, `Pp2-pd`, `Pp2-pl`, `Pp2-pn`, `Pp2-sa`, `Pp2-sd`, `Pp2-sg`, `Pp2-sl`, `Pp2-sn`, `Pp3-pa`, `Pp3-pd`, `Pp3-pg`, `Pp3-pi`, `Pp3-pl`, `Pp3fpn`, `Pp3fsa`, `Pp3fsd`, `Pp3fsg`, `Pp3fsi`, `Pp3fsl`, `Pp3fsn`, `Pp3mpn`, `Pp3msa`, `Pp3msd`, `Pp3msg`, `Pp3msi`, `Pp3msl`, `Pp3msn`, `Pp3npn`, `Pp3nsa`, `Pp3nsi`, `Pp3nsn`, `Pq-fpa`, `Pq-fpn`, `Pq-fsa`, `Pq-fsi`, `Pq-fsl`, `Pq-fsn`, `Pq-mpn`, `Pq-msn`, `Pq-nsn`, `Pq3m-d`, `Pq3m-n`, `Pq3n-a`, `Pq3n-l`, `Pq3n-n`, `Ps1fpa`, `Ps1fpg`, `Ps1fpl`, `Ps1fpn`, `Ps1fsa`, `Ps1fsd`, `Ps1fsg`, `Ps1fsi`, `Ps1fsl`, `Ps1fsn`, _(truncated: full list in pipeline meta)_ | | **`morphologizer`** | `Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Loc\|POS=ADP`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Ins\|POS=ADP`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Degree=Pos\|POS=ADV`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=NOUN`, `POS=PUNCT`, `POS=PART`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=SCONJ`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=CCONJ`, `Case=Gen\|POS=ADP`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `POS=VERB\|VerbForm=Inf`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `POS=PART\|Polarity=Neg`, `Case=Acc\|Gender=Neut\|POS=PRON\|PronType=Neg`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Degree=Pos\|POS=ADV\|PronType=Dem`, `Degree=Cmp\|POS=ADV`, `Case=Acc\|POS=ADP`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `NumType=Ord\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Gender=Fem\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|POS=PRON\|PronType=Int,Rel`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Gender=Fem\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `NumType=Card\|POS=NUM`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Degree=Pos\|POS=ADV\|PronType=Int,Rel`, `Gender=Neut\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Gender=Masc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Gen\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Loc\|Gender=Neut\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `POS=X`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Definite=Def\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Gen\|Gender=Neut\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Anim\|Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `POS=AUX\|VerbForm=Inf`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Gender=Fem\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Degree=Pos\|POS=ADV\|PronType=Ind`, `Animacy=Inan\|Case=Acc\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Degree=Pos\|POS=ADV\|PronType=Neg`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Masc\|POS=PRON\|PronType=Neg`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `POS=NOUN`, `Case=Voc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Acc\|Gender=Masc\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Loc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Loc\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=NOUN`, `POS=SPACE`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|POS=PRON\|PronType=Ind`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Animacy=Inan\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Gender=Masc\|POS=PRON\|PronType=Neg`, `Case=Ins\|Gender=Neut\|POS=PRON\|PronType=Int,Rel`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|POS=ADP`, `Degree=Sup\|POS=ADV`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `POS=ADV\|Tense=Pres\|VerbForm=Conv`, `Case=Ins\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Neut\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Fem\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `NumType=Mult\|POS=NUM`, `Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Fem\|NumType=Mult\|POS=NUM`, `Case=Acc\|Gender=Neut\|POS=PRON\|PronType=Int,Rel`, `Animacy=Inan\|Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|NumType=Mult\|POS=NUM`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Loc\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Dat\|Gender=Masc\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Loc\|Gender=Neut\|POS=PRON\|PronType=Int,Rel`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `POS=ADV\|Tense=Past\|VerbForm=Conv`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|POS=PRON\|PronType=Int,Rel`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Definite=Def\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Ins\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Degree=Pos\|POS=ADV\|PronType=Tot`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Gender=Masc\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Ins\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Dat\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Ins\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|POS=PRON\|PronType=Neg`, `Case=Gen\|Gender=Masc\|NumType=Mult\|POS=NUM`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Animacy=Inan\|Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Gender=Neut\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Ins\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Neut\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|POS=PRON\|PronType=Ind`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Int,Rel`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Ins\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Gen\|Gender=Masc\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `NumType=Mult\|POS=SYM`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Masc\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Loc\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int,Rel`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Nom\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Nom\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=2\|Tense=Past\|VerbForm=Fin`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Neg`, `Case=Loc\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=SYM`, `Case=Ins\|Definite=Def\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Gen\|Gender=Fem\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Anim\|Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Gender=Masc\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int,Rel`, `Case=Ins\|Definite=Def\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Definite=Def\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Gen\|Definite=Def\|Degree=Sup\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Acc\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Neut\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|NumType=Card\|Number=Plur\|POS=NUM`, `Animacy=Anim\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Gender[psor]=Masc,Neut\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Anim\|Case=Acc\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Ind\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Nom\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Definite=Def\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Dat\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, _(truncated: full list in pipeline meta)_ | | **`parser`** | `ROOT`, `acl`, `advcl`, `advmod`, `advmod:emph`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `ccomp`, `compound`, `conj`, `cop`, `csubj`, `csubj:pass`, `dep`, `det`, `discourse`, `expl:pv`, `fixed`, `flat`, `flat:foreign`, `goeswith`, `iobj`, `mark`, `nmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `orphan`, `parataxis`, `punct`, `xcomp` | | **`ner`** | `DERIV_PER`, `LOC`, `MISC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.89 | | `TOKEN_P` | 97.28 | | `TOKEN_R` | 98.71 | | `TOKEN_F` | 97.99 | | `TAG_ACC` | 90.03 | | `POS_ACC` | 96.74 | | `MORPH_ACC` | 90.62 | | `MORPH_MICRO_P` | 94.88 | | `MORPH_MICRO_R` | 94.34 | | `MORPH_MICRO_F` | 94.61 | | `SENTS_P` | 94.95 | | `SENTS_R` | 94.72 | | `SENTS_F` | 94.84 | | `DEP_UAS` | 84.47 | | `DEP_LAS` | 77.65 | | `LEMMA_ACC` | 91.94 | | `ENTS_P` | 77.38 | | `ENTS_R` | 75.45 | | `ENTS_F` | 76.40 |
spacy/it_core_news_sm
spacy
2023-10-10T06:46:05Z
62
2
spacy
[ "spacy", "token-classification", "it", "license:cc-by-nc-sa-3.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - it license: cc-by-nc-sa-3.0 model-index: - name: it_core_news_sm results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8600824654 - name: NER Recall type: recall value: 0.8579197692 - name: NER F Score type: f_score value: 0.858999756 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9650368506 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9701163888 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9701573034 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.969356578 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8969952665 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8575397438 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9796640141 --- ### Details: https://spacy.io/models/it#it_core_news_sm Italian pipeline optimized for CPU. Components: tok2vec, morphologizer, tagger, parser, lemmatizer (trainable_lemmatizer), senter, ner. | Feature | Description | | --- | --- | | **Name** | `it_core_news_sm` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | | **Sources** | [UD Italian ISDT v2.8](https://github.com/UniversalDependencies/UD_Italian-ISDT) (Bosco, Cristina; Lenci, Alessandro; Montemagni, Simonetta; Simi, Maria)<br />[WikiNER](https://figshare.com/articles/Learning_multilingual_named_entity_recognition_from_Wikipedia/5462500) (Joel Nothman, Nicky Ringland, Will Radford, Tara Murphy, James R Curran) | | **License** | `CC BY-NC-SA 3.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (443 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `POS=PROPN`, `POS=PUNCT`, `Gender=Masc\|POS=NOUN`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=ADP\|PronType=Art`, `Gender=Fem\|Number=Sing\|POS=NOUN`, `Gender=Masc\|Number=Sing\|POS=ADJ`, `Gender=Masc\|Number=Sing\|POS=NOUN`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part`, `POS=AUX\|VerbForm=Inf`, `Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `POS=ADP`, `Gender=Fem\|Number=Sing\|POS=ADJ`, `POS=PRON\|PronType=Rel`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Plur\|POS=NOUN`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Ind`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=ADP\|PronType=Art`, `Number=Plur\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Definite=Def\|Number=Sing\|POS=DET\|PronType=Art`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `POS=VERB\|VerbForm=Inf`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Number=Sing\|POS=ADJ`, `POS=CCONJ`, `NumType=Card\|POS=NUM`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=ADP\|PronType=Art`, `Definite=Def\|Gender=Fem\|Number=Plur\|POS=ADP\|PronType=Art`, `Gender=Fem\|Number=Plur\|POS=NOUN`, `Clitic=Yes\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Fem\|Number=Plur\|POS=ADJ`, `Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|Number=Plur\|POS=ADJ`, `POS=SPACE`, `Definite=Def\|Number=Sing\|POS=ADP\|PronType=Art`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|NumType=Ord\|Number=Sing\|POS=ADJ`, `POS=ADV`, `POS=NOUN`, `Number=Sing\|POS=NOUN`, `POS=VERB\|VerbForm=Ger`, `Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `POS=INTJ`, `Clitic=Yes\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Part`, `Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|POS=NOUN`, `Gender=Fem\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Ind`, `Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Number=Plur\|POS=NOUN`, `POS=SCONJ`, `Number=Sing\|POS=DET\|PronType=Ind`, `POS=ADV\|PronType=Neg`, `Clitic=Yes\|POS=VERB\|PronType=Prs\|VerbForm=Inf`, `Gender=Fem\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Part`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Ind`, `POS=ADJ`, `Number=Sing\|POS=PRON\|PronType=Rel`, `Gender=Fem\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Number=Sing\|POS=PRON\|PronType=Ind`, `Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Part`, `Clitic=Yes\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `POS=DET\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Clitic=Yes\|Gender=Masc\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Clitic=Yes\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Clitic=Yes\|POS=PRON\|PronType=Prs`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Clitic=Yes\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Clitic=Yes\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Degree=Cmp\|Number=Plur\|POS=ADJ`, `Clitic=Yes\|Gender=Masc\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Degree=Cmp\|Number=Sing\|POS=ADJ`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Degree=Abs\|POS=ADV`, `Clitic=Yes\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Gender=Masc\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `POS=DET\|PronType=Exc`, `Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Number=Sing\|POS=DET\|PronType=Dem`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Gender=Fem\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Number=Sing\|POS=DET\|PronType=Int`, `POS=PRON\|PronType=Int`, `Clitic=Yes\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Ind`, `Number=Sing\|POS=ADP`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Foreign=Yes\|POS=X`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Clitic=Yes\|POS=AUX\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Clitic=Yes\|Gender=Masc\|Mood=Imp\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Part`, `POS=INTJ\|Polarity=Neg`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|PronType=Rel`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Rel`, `Clitic=Yes\|Number=Plur\|POS=VERB\|Person=1\|PronType=Prs\|VerbForm=Ger`, `POS=INTJ\|Polarity=Pos`, `Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `POS=DET\|PronType=Int`, `Gender=Masc\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `POS=PRON\|Person=3\|PronType=Prs`, `Degree=Abs\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Dem`, `Clitic=Yes\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Clitic=Yes\|Gender=Fem\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Clitic=Yes\|Gender=Fem\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Degree=Abs\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Clitic=Yes\|POS=AUX\|PronType=Prs\|VerbForm=Inf`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Tot`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Dem`, `Degree=Abs\|Gender=Masc\|Number=Sing\|POS=ADJ`, `NumType=Ord\|POS=ADJ`, `POS=DET\|PronType=Rel`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Rel`, `Gender=Masc\|Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Clitic=Yes\|Number=Sing\|POS=VERB\|Person=1\|PronType=Prs\|VerbForm=Inf`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Fut\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|POS=VERB\|PronType=Prs\|VerbForm=Ger`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Gender=Masc\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Part`, `Number=Sing\|POS=PRON\|PronType=Int`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Clitic=Yes\|Number=Plur\|POS=VERB\|Person=2\|PronType=Prs\|VerbForm=Inf`, `Clitic=Yes\|Number=Plur\|POS=VERB\|Person=1\|PronType=Prs\|VerbForm=Inf`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Fut\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Definite=Def\|POS=DET\|PronType=Art`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `POS=SYM`, `Clitic=Yes\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Gender=Masc\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=2,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Fut\|VerbForm=Fin`, `Clitic=Yes\|Gender=Fem\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Degree=Abs\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Number=Sing\|POS=PRON\|PronType=Dem`, `POS=AUX\|VerbForm=Ger`, `Gender=Masc\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Clitic=Yes\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|VerbForm=Inf`, `POS=PRON\|PronType=Ind`, `Clitic=Yes\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=1\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `POS=X`, `Gender=Masc\|POS=ADJ`, `Clitic=Yes\|Gender=Fem\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Number=Sing\|POS=VERB\|Person=2\|PronType=Prs\|VerbForm=Inf`, `Clitic=Yes\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Part`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=2\|Tense=Imp\|VerbForm=Fin`, `POS=PART`, `Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part`, `NumType=Ord\|Number=Sing\|POS=ADJ`, `Number=Plur\|POS=DET\|PronType=Int`, `Clitic=Yes\|Mood=Sub\|Number=Plur\|POS=VERB\|Person=1\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Number=Plur\|POS=DET\|PronType=Rel`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Clitic=Yes\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Clitic=Yes\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Clitic=Yes\|Number=Sing\|POS=VERB\|Person=1\|PronType=Prs\|VerbForm=Ger`, `Clitic=Yes\|Number=Sing\|POS=AUX\|Person=1\|PronType=Prs\|VerbForm=Ger`, `Clitic=Yes\|Gender=Masc\|Number=Plur\|POS=AUX\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Clitic=Yes\|Mood=Imp\|Number=Plur,Sing\|POS=VERB\|Person=1,2\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Mood=Imp\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `NumType=Range\|POS=NUM`, `Number=Plur\|POS=PRON\|PronType=Dem`, `POS=VERB\|Tense=Past\|VerbForm=Part`, `Clitic=Yes\|POS=ADV\|PronType=Prs`, `Clitic=Yes\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|POS=PRON\|PronType=Rel`, `Clitic=Yes\|Gender=Masc\|Mood=Imp\|Number=Plur,Sing\|POS=VERB\|Person=2,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Number=Sing\|POS=AUX\|Person=2\|PronType=Prs\|VerbForm=Inf`, `Clitic=Yes\|Number=Sing\|POS=VERB\|Person=2\|PronType=Prs\|VerbForm=Ger`, `Mood=Imp\|Number=Sing\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Gender=Fem\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=2,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Clitic=Yes\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Part`, `Clitic=Yes\|Gender=Masc\|Number=Plur,Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Definite=Ind\|POS=DET\|PronType=Art`, `Clitic=Yes\|Gender=Fem,Masc\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Part`, `Definite=Ind\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Definite=Def\|Number=Plur\|POS=ADP\|PronType=Art`, `Clitic=Yes\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `POS=DET\|PronType=Ind`, `Number=Plur\|POS=DET\|PronType=Dem`, `Clitic=Yes\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Plur\|POS=DET\|PronType=Tot`, `Clitic=Yes\|POS=AUX\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Number=Plur\|POS=PRON\|PronType=Ind`, `Clitic=Yes\|Gender=Fem,Masc\|Number=Plur,Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Part`, `Clitic=Yes\|Number=Plur\|POS=VERB\|PronType=Prs\|VerbForm=Inf`, `Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Number=Plur\|POS=ADP`, `Clitic=Yes\|Gender=Masc\|Number=Sing\|POS=ADV\|Person=3\|PronType=Prs`, `Clitic=Yes\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=1,2\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Part`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Gender=Fem\|Number=Plur\|POS=ADV\|Person=3\|PronType=Prs`, `POS=DET\|PronType=Tot`, `POS=PRON\|PronType=Dem`, `Clitic=Yes\|Gender=Masc\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=2,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Definite=Ind\|Number=Sing\|POS=DET\|PronType=Art`, `NumType=Ord\|POS=NUM`, `Clitic=Yes\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Gender=Masc\|POS=DET\|PronType=Dem`, `Clitic=Yes\|Gender=Masc\|Number=Plur,Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Part`, `Gender=Masc\|Number=Sing\|POS=NOUN\|Tense=Past\|VerbForm=Part`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Int`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Int`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Int`, `Number=Plur\|POS=PRON\|PronType=Int`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Int`, `Clitic=Yes\|Number=Plur\|POS=PRON\|PronType=Prs`, `Foreign=Yes\|Number=Sing\|POS=X`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Fut\|VerbForm=Fin`, `POS=PRON\|PronType=Prs`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Tense=Imp\|VerbForm=Fin`, `POS=SCONJ\|PronType=Rel`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `POS=PRON\|Person=3\|PronType=Rel`, `Clitic=Yes\|Number=Plur\|POS=VERB\|Person=2\|PronType=Prs\|VerbForm=Ger`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin`, `Clitic=Yes\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Degree=Cmp\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Fut\|VerbForm=Fin`, `Definite=Def\|Number=Plur\|POS=DET\|PronType=Art`, `Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=ADP`, `Gender=Fem\|POS=ADJ`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Gender=Fem\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=2,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|POS=DET\|Poss=Yes\|PronType=Prs`, `Gender=Fem\|Number=Plur\|POS=PROPN`, `Definite=Ind\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Number=Sing\|POS=DET\|PronType=Art`, `Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes\|PronType=Prs`, `Foreign=Yes\|POS=NOUN`, `Clitic=Yes\|Gender=Fem\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Clitic=Yes\|Gender=Masc\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=DET`, `Clitic=Yes\|Gender=Fem\|Mood=Imp\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=DET`, `Number=Sing\|POS=X`, `Foreign=Yes\|Gender=Masc\|POS=X`, `Clitic=Yes\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Prs`, `Clitic=Yes\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Prs`, `Clitic=Yes\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Art`, `Gender=Masc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin`, `Definite=Def\|Gender=Fem\|POS=DET`, `Definite=Def\|POS=DET`, `Foreign=Yes\|POS=PROPN`, `NumType=Card\|POS=PROPN`, `Gender=Fem\|Number=Sing\|POS=DET`, `Degree=Abs\|Gender=Masc\|Number=Sing\|POS=ADV`, `Gender=Masc\|Number=Plur\|POS=NOUN\|Tense=Past\|VerbForm=Part`, `Mood=Imp\|Number=Plur\|POS=VERB\|Person=2`, `Clitic=Yes\|Number=Plur\|POS=AUX\|Person=1\|PronType=Prs\|VerbForm=Inf`, `Gender=Masc\|Number=Sing\|POS=DET`, `Number=Sing\|POS=DET`, `Gender=Masc\|Number=Sing\|POS=PRON`, `POS=DET` | | **`tagger`** | `A`, `AP`, `B`, `BN`, `B_PC`, `CC`, `CS`, `DD`, `DE`, `DI`, `DQ`, `DR`, `E`, `E_RD`, `FB`, `FC`, `FF`, `FS`, `I`, `N`, `NO`, `PART`, `PC`, `PC_PC`, `PD`, `PE`, `PI`, `PP`, `PQ`, `PR`, `RD`, `RI`, `S`, `SP`, `SW`, `SYM`, `T`, `V`, `VA`, `VA_PC`, `VM`, `VM_PC`, `VM_PC_PC`, `V_B`, `V_PC`, `V_PC_PC`, `X`, `_SP` | | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `ccomp`, `compound`, `conj`, `cop`, `csubj`, `dep`, `det`, `det:poss`, `det:predet`, `discourse`, `expl`, `expl:impers`, `expl:pass`, `fixed`, `flat`, `flat:foreign`, `flat:name`, `iobj`, `mark`, `nmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `obl:agent`, `parataxis`, `punct`, `vocative`, `xcomp` | | **`ner`** | `LOC`, `MISC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.93 | | `TOKEN_P` | 99.80 | | `TOKEN_R` | 99.78 | | `TOKEN_F` | 99.79 | | `POS_ACC` | 97.01 | | `MORPH_ACC` | 97.02 | | `MORPH_MICRO_P` | 98.53 | | `MORPH_MICRO_R` | 97.73 | | `MORPH_MICRO_F` | 98.12 | | `TAG_ACC` | 96.50 | | `SENTS_P` | 97.71 | | `SENTS_R` | 98.23 | | `SENTS_F` | 97.97 | | `DEP_UAS` | 89.70 | | `DEP_LAS` | 85.75 | | `LEMMA_ACC` | 96.94 | | `ENTS_P` | 86.01 | | `ENTS_R` | 85.79 | | `ENTS_F` | 85.90 |
spacy/ja_core_news_md
spacy
2023-10-10T06:45:12Z
6
0
spacy
[ "spacy", "token-classification", "ja", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - ja license: cc-by-sa-4.0 model-index: - name: ja_core_news_md results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7266576455 - name: NER Recall type: recall value: 0.6754716981 - name: NER F Score type: f_score value: 0.7001303781 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9713282143 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9712018326 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.0 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9670499959 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.9221346544 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.9092381767 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9696376102 --- ### Details: https://spacy.io/models/ja#ja_core_news_md Japanese pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler. | Feature | Description | | --- | --- | | **Name** | `ja_core_news_md` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 480443 keys, 20000 unique vectors (300 dimensions) | | **Sources** | [UD Japanese GSD v2.8](https://github.com/UniversalDependencies/UD_Japanese-GSD) (Omura, Mai; Miyao, Yusuke; Kanayama, Hiroshi; Matsuda, Hiroshi; Wakasa, Aya; Yamashita, Kayo; Asahara, Masayuki; Tanaka, Takaaki; Murawaki, Yugo; Matsumoto, Yuji; Mori, Shinsuke; Uematsu, Sumire; McDonald, Ryan; Nivre, Joakim; Zeman, Daniel)<br />[UD Japanese GSD v2.8 NER](https://github.com/megagonlabs/UD_Japanese-GSD) (Megagon Labs Tokyo)<br />[chiVe: Japanese Word Embedding with Sudachi & NWJC (chive-1.1-mc90-500k)](https://github.com/WorksApplications/chiVe) (Works Applications) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (65 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `POS=NOUN`, `POS=ADP`, `POS=VERB`, `POS=SCONJ`, `POS=AUX`, `POS=PUNCT`, `POS=PART`, `POS=DET`, `POS=NUM`, `POS=ADV`, `POS=PRON`, `POS=ADJ`, `POS=PROPN`, `POS=CCONJ`, `POS=SYM`, `POS=NOUN\|Polarity=Neg`, `POS=AUX\|Polarity=Neg`, `POS=SPACE`, `POS=INTJ`, `POS=SCONJ\|Polarity=Neg` | | **`parser`** | `ROOT`, `acl`, `advcl`, `advmod`, `amod`, `aux`, `case`, `cc`, `ccomp`, `compound`, `cop`, `csubj`, `dep`, `det`, `dislocated`, `fixed`, `mark`, `nmod`, `nsubj`, `nummod`, `obj`, `obl`, `punct` | | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `MOVEMENT`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PET_NAME`, `PHONE`, `PRODUCT`, `QUANTITY`, `TIME`, `TITLE_AFFIX`, `WORK_OF_ART` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.37 | | `TOKEN_P` | 97.64 | | `TOKEN_R` | 97.88 | | `TOKEN_F` | 97.76 | | `POS_ACC` | 97.12 | | `MORPH_ACC` | 0.00 | | `MORPH_MICRO_P` | 34.01 | | `MORPH_MICRO_R` | 98.04 | | `MORPH_MICRO_F` | 50.51 | | `SENTS_P` | 96.30 | | `SENTS_R` | 97.63 | | `SENTS_F` | 96.96 | | `DEP_UAS` | 92.21 | | `DEP_LAS` | 90.92 | | `TAG_ACC` | 97.13 | | `LEMMA_ACC` | 96.70 | | `ENTS_P` | 72.67 | | `ENTS_R` | 67.55 | | `ENTS_F` | 70.01 |
spacy/ko_core_news_sm
spacy
2023-10-10T06:44:26Z
50
1
spacy
[ "spacy", "token-classification", "ko", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-05-02T08:18:16Z
--- tags: - spacy - token-classification language: - ko license: cc-by-sa-4.0 model-index: - name: ko_core_news_sm results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7704418068 - name: NER Recall type: recall value: 0.6603320381 - name: NER F Score type: f_score value: 0.7111499981 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.7305919816 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.8582222398 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.8356969086 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.7360798556 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.6558677391 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.999274135 --- ### Details: https://spacy.io/models/ko#ko_core_news_sm Korean pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner. | Feature | Description | | --- | --- | | **Name** | `ko_core_news_sm` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | | **Sources** | [UD Korean Kaist v2.8](https://github.com/UniversalDependencies/UD_Korean-Kaist) (Choi, Jinho; Han, Na-Rae; Hwang, Jena; Chun, Jayeol)<br />[KLUE v1.1.0](https://github.com/KLUE-benchmark/KLUE) (Sungjoon Park, Jihyung Moon, Sungdong Kim, Won Ik Cho, Jiyoon Han, Jangwon Park, Chisung Song, Junseong Kim, Youngsook Song, Taehwan Oh, Joohong Lee, Juhyun Oh, Sungwon Ryu, Younghoon Jeong, Inkwon Lee, Sangwoo Seo, Dongjun Lee, Hyunwoo Kim, Myeonghwa Lee, Seongbo Jang, Seungwon Do, Sunkyoung Kim, Kyungtae Lim, Jongwon Lee, Kyumin Park, Jamin Shin, Seonghyun Kim, Lucy Park, Alice Oh, Jung-Woo Ha, Kyunghyun Cho) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (2028 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `_SP`, `ecs`, `etm`, `f`, `f+f+jcj`, `f+f+jcs`, `f+f+jct`, `f+f+jxt`, `f+jca`, `f+jca+jp+ecc`, `f+jca+jp+ep+ef`, `f+jca+jxc`, `f+jca+jxc+jcm`, `f+jca+jxt`, `f+jcj`, `f+jcm`, `f+jco`, `f+jcs`, `f+jct`, `f+jct+jcm`, `f+jp+ef`, `f+jp+ep+ef`, `f+jp+etm`, `f+jxc`, `f+jxt`, `f+ncn`, `f+ncn+jcm`, `f+ncn+jcs`, `f+ncn+jp+ecc`, `f+ncn+jxt`, `f+ncpa+jcm`, `f+npp+jcs`, `f+nq`, `f+xsn`, `f+xsn+jco`, `f+xsn+jxt`, `ii`, `jca`, `jca+jcm`, `jca+jxc`, `jca+jxt`, `jcc`, `jcj`, `jcm`, `jco`, `jcr`, `jcr+jxc`, `jcs`, `jct`, `jct+jcm`, `jct+jxt`, `jp+ecc`, `jp+ecs`, `jp+ef`, `jp+ef+jcr`, `jp+ef+jcr+jxc`, `jp+ep+ecs`, `jp+ep+ef`, `jp+ep+etm`, `jp+ep+etn`, `jp+etm`, `jp+etn`, `jp+etn+jco`, `jp+etn+jxc`, `jxc`, `jxc+jca`, `jxc+jco`, `jxc+jcs`, `jxt`, `mad`, `mad+jxc`, `mad+jxt`, `mag`, `mag+jca`, `mag+jcm`, `mag+jcs`, `mag+jp+ef+jcr`, `mag+jxc`, `mag+jxc+jxc`, `mag+jxt`, `mag+xsn`, `maj`, `maj+jxc`, `maj+jxt`, `mma`, `mmd`, `nbn`, `nbn+jca`, `nbn+jca+jcj`, `nbn+jca+jcm`, `nbn+jca+jp+ef`, `nbn+jca+jxc`, `nbn+jca+jxt`, `nbn+jcc`, `nbn+jcj`, `nbn+jcm`, `nbn+jco`, `nbn+jcr`, `nbn+jcs`, `nbn+jct`, `nbn+jct+jcm`, `nbn+jct+jxt`, `nbn+jp+ecc`, `nbn+jp+ecs`, `nbn+jp+ecs+jca`, `nbn+jp+ecs+jcm`, `nbn+jp+ecs+jco`, `nbn+jp+ecs+jxc`, `nbn+jp+ecs+jxt`, `nbn+jp+ecx`, `nbn+jp+ef`, `nbn+jp+ef+jca`, `nbn+jp+ef+jco`, `nbn+jp+ef+jcr`, `nbn+jp+ef+jcr+jxc`, `nbn+jp+ef+jcr+jxt`, `nbn+jp+ef+jcs`, `nbn+jp+ef+jxc`, `nbn+jp+ef+jxc+jco`, `nbn+jp+ef+jxf`, `nbn+jp+ef+jxt`, `nbn+jp+ep+ecc`, `nbn+jp+ep+ecs`, `nbn+jp+ep+ecs+jxc`, `nbn+jp+ep+ef`, `nbn+jp+ep+ef+jcr`, `nbn+jp+ep+etm`, `nbn+jp+ep+etn`, `nbn+jp+ep+etn+jco`, `nbn+jp+ep+etn+jcs`, `nbn+jp+etm`, `nbn+jp+etn`, `nbn+jp+etn+jca`, `nbn+jp+etn+jca+jxt`, `nbn+jp+etn+jco`, `nbn+jp+etn+jcs`, `nbn+jp+etn+jxc`, `nbn+jp+etn+jxt`, `nbn+jxc`, `nbn+jxc+jca`, `nbn+jxc+jca+jxc`, `nbn+jxc+jca+jxt`, `nbn+jxc+jcc`, `nbn+jxc+jcm`, `nbn+jxc+jco`, `nbn+jxc+jcs`, `nbn+jxc+jp+ef`, `nbn+jxc+jxc`, `nbn+jxc+jxt`, `nbn+jxt`, `nbn+nbn`, `nbn+nbn+jp+ef`, `nbn+xsm+ecs`, `nbn+xsm+ef`, `nbn+xsm+ep+ef`, `nbn+xsm+ep+ef+jcr`, `nbn+xsm+etm`, `nbn+xsn`, `nbn+xsn+jca`, `nbn+xsn+jca+jp+ef+jcr`, `nbn+xsn+jca+jxc`, `nbn+xsn+jca+jxt`, `nbn+xsn+jcm`, `nbn+xsn+jco`, `nbn+xsn+jcs`, `nbn+xsn+jct`, `nbn+xsn+jp+ecc`, `nbn+xsn+jp+ecs`, `nbn+xsn+jp+ef`, `nbn+xsn+jp+ef+jcr`, `nbn+xsn+jp+ep+ef`, `nbn+xsn+jxc`, `nbn+xsn+jxt`, `nbn+xsv+etm`, `nbu`, `nbu+jca`, `nbu+jca+jxc`, `nbu+jca+jxt`, `nbu+jcc`, `nbu+jcc+jxc`, `nbu+jcj`, `nbu+jcm`, `nbu+jco`, `nbu+jcs`, `nbu+jct`, `nbu+jct+jxc`, `nbu+jp+ecc`, `nbu+jp+ecs`, `nbu+jp+ef`, `nbu+jp+ef+jcr`, `nbu+jp+ef+jxc`, `nbu+jp+ep+ecc`, `nbu+jp+ep+ecs`, `nbu+jp+ep+ef`, `nbu+jp+ep+ef+jcr`, `nbu+jp+ep+etm`, `nbu+jp+ep+etn+jco`, `nbu+jp+etm`, `nbu+jxc`, `nbu+jxc+jca`, `nbu+jxc+jcs`, `nbu+jxc+jp+ef`, `nbu+jxc+jp+ep+ef`, `nbu+jxc+jxt`, `nbu+jxt`, `nbu+ncn`, `nbu+ncn+jca`, `nbu+ncn+jcm`, `nbu+xsn`, `nbu+xsn+jca`, `nbu+xsn+jca+jxc`, `nbu+xsn+jca+jxt`, `nbu+xsn+jcm`, `nbu+xsn+jco`, `nbu+xsn+jcs`, `nbu+xsn+jp+ecs`, `nbu+xsn+jp+ep+ef`, `nbu+xsn+jxc`, `nbu+xsn+jxc+jxt`, `nbu+xsn+jxt`, `nbu+xsv+ecc`, `nbu+xsv+etm`, `ncn`, `ncn+f+ncpa+jco`, `ncn+jca`, `ncn+jca+jca`, `ncn+jca+jcc`, `ncn+jca+jcj`, `ncn+jca+jcm`, `ncn+jca+jcs`, `ncn+jca+jct`, `ncn+jca+jp+ecc`, `ncn+jca+jp+ecs`, `ncn+jca+jp+ef`, `ncn+jca+jp+ep+ef`, `ncn+jca+jp+etm`, `ncn+jca+jp+etn+jxt`, `ncn+jca+jxc`, `ncn+jca+jxc+jcc`, `ncn+jca+jxc+jcm`, `ncn+jca+jxc+jxc`, `ncn+jca+jxc+jxt`, `ncn+jca+jxt`, `ncn+jcc`, `ncn+jcc+jxc`, `ncn+jcj`, `ncn+jcj+jxt`, `ncn+jcm`, `ncn+jco`, `ncn+jcr`, `ncn+jcr+jxc`, `ncn+jcs`, `ncn+jcs+jxt`, `ncn+jct`, `ncn+jct+jcm`, `ncn+jct+jxc`, `ncn+jct+jxt`, `ncn+jcv`, `ncn+jp+ecc`, `ncn+jp+ecc+jct`, `ncn+jp+ecc+jxc`, `ncn+jp+ecs`, `ncn+jp+ecs+jcm`, `ncn+jp+ecs+jco`, `ncn+jp+ecs+jxc`, `ncn+jp+ecs+jxt`, `ncn+jp+ecx`, `ncn+jp+ef`, `ncn+jp+ef+jca`, `ncn+jp+ef+jcm`, `ncn+jp+ef+jco`, `ncn+jp+ef+jcr`, `ncn+jp+ef+jcr+jxc`, `ncn+jp+ef+jcr+jxt`, `ncn+jp+ef+jp+etm`, `ncn+jp+ef+jxc`, `ncn+jp+ef+jxf`, `ncn+jp+ef+jxt`, `ncn+jp+ep+ecc`, `ncn+jp+ep+ecs`, `ncn+jp+ep+ecs+jxc`, `ncn+jp+ep+ecx`, `ncn+jp+ep+ef`, `ncn+jp+ep+ef+jcr`, `ncn+jp+ep+ef+jcr+jxc`, `ncn+jp+ep+ef+jxc`, `ncn+jp+ep+ef+jxf`, `ncn+jp+ep+ef+jxt`, `ncn+jp+ep+ep+etm`, `ncn+jp+ep+etm`, `ncn+jp+ep+etn`, `ncn+jp+ep+etn+jca`, `ncn+jp+ep+etn+jca+jxc`, `ncn+jp+ep+etn+jco`, `ncn+jp+ep+etn+jcs`, `ncn+jp+ep+etn+jxt`, `ncn+jp+etm`, `ncn+jp+etn`, `ncn+jp+etn+jca`, `ncn+jp+etn+jca+jxc`, `ncn+jp+etn+jca+jxt`, `ncn+jp+etn+jco`, `ncn+jp+etn+jcs`, `ncn+jp+etn+jct`, `ncn+jp+etn+jxc`, `ncn+jp+etn+jxt`, `ncn+jxc`, `ncn+jxc+jca`, `ncn+jxc+jca+jxc`, `ncn+jxc+jca+jxt`, `ncn+jxc+jcc`, `ncn+jxc+jcm`, `ncn+jxc+jco`, `ncn+jxc+jcs`, `ncn+jxc+jct+jxt`, `ncn+jxc+jp+ef`, `ncn+jxc+jp+ef+jcr`, `ncn+jxc+jp+ep+ecs`, `ncn+jxc+jp+ep+ef`, `ncn+jxc+jp+etm`, `ncn+jxc+jxc`, `ncn+jxc+jxt`, `ncn+jxt`, `ncn+jxt+jcm`, `ncn+jxt+jxc`, `ncn+nbn`, `ncn+nbn+jca`, `ncn+nbn+jcm`, `ncn+nbn+jcs`, `ncn+nbn+jp+ecc`, `ncn+nbn+jp+ep+ef`, `ncn+nbn+jxc`, `ncn+nbn+jxt`, `ncn+nbu`, `ncn+nbu+jca`, `ncn+nbu+jcm`, `ncn+nbu+jco`, `ncn+nbu+jp+ef`, `ncn+nbu+jxc`, `ncn+nbu+ncn`, `ncn+ncn`, `ncn+ncn+jca`, `ncn+ncn+jca+jcc`, `ncn+ncn+jca+jcm`, `ncn+ncn+jca+jxc`, `ncn+ncn+jca+jxc+jcm`, `ncn+ncn+jca+jxc+jxc`, `ncn+ncn+jca+jxt`, `ncn+ncn+jcc`, `ncn+ncn+jcj`, `ncn+ncn+jcm`, `ncn+ncn+jco`, `ncn+ncn+jcr`, `ncn+ncn+jcs`, `ncn+ncn+jct`, `ncn+ncn+jct+jcm`, `ncn+ncn+jct+jxc`, `ncn+ncn+jct+jxt`, `ncn+ncn+jp+ecc`, `ncn+ncn+jp+ecs`, `ncn+ncn+jp+ef`, `ncn+ncn+jp+ef+jcm`, `ncn+ncn+jp+ef+jcr`, `ncn+ncn+jp+ef+jcs`, `ncn+ncn+jp+ep+ecc`, `ncn+ncn+jp+ep+ecs`, `ncn+ncn+jp+ep+ef`, `ncn+ncn+jp+ep+ef+jcr`, `ncn+ncn+jp+ep+ep+etm`, `ncn+ncn+jp+ep+etm`, `ncn+ncn+jp+ep+etn`, `ncn+ncn+jp+etm`, `ncn+ncn+jp+etn`, `ncn+ncn+jp+etn+jca`, `ncn+ncn+jp+etn+jco`, `ncn+ncn+jp+etn+jxc`, `ncn+ncn+jxc`, `ncn+ncn+jxc+jca`, `ncn+ncn+jxc+jcc`, `ncn+ncn+jxc+jcm`, `ncn+ncn+jxc+jco`, `ncn+ncn+jxc+jcs`, `ncn+ncn+jxc+jxc`, `ncn+ncn+jxt`, `ncn+ncn+nbn`, `ncn+ncn+ncn`, `ncn+ncn+ncn+jca`, `ncn+ncn+ncn+jca+jcm`, `ncn+ncn+ncn+jca+jxt`, `ncn+ncn+ncn+jcj`, `ncn+ncn+ncn+jcm`, `ncn+ncn+ncn+jco`, `ncn+ncn+ncn+jcs`, `ncn+ncn+ncn+jct+jxt`, `ncn+ncn+ncn+jp+etn+jxc`, `ncn+ncn+ncn+jxt`, `ncn+ncn+ncn+ncn+jca`, `ncn+ncn+ncn+ncn+jca+jxt`, `ncn+ncn+ncn+ncn+jco`, `ncn+ncn+ncn+xsn+jp+etm`, `ncn+ncn+ncpa`, `ncn+ncn+ncpa+jca`, `ncn+ncn+ncpa+jcm`, `ncn+ncn+ncpa+jco`, `ncn+ncn+ncpa+jcs`, `ncn+ncn+ncpa+jxc`, `ncn+ncn+ncpa+jxt`, `ncn+ncn+ncpa+ncn`, `ncn+ncn+ncpa+ncn+jca`, `ncn+ncn+ncpa+ncn+jcj`, `ncn+ncn+ncpa+ncn+jcm`, `ncn+ncn+ncpa+ncn+jxt`, `ncn+ncn+xsn`, `ncn+ncn+xsn+jca`, `ncn+ncn+xsn+jca+jxt`, `ncn+ncn+xsn+jcj`, `ncn+ncn+xsn+jcm`, `ncn+ncn+xsn+jco`, `ncn+ncn+xsn+jcs`, `ncn+ncn+xsn+jct`, `ncn+ncn+xsn+jp+ecs`, `ncn+ncn+xsn+jp+ep+ef`, `ncn+ncn+xsn+jp+etm`, `ncn+ncn+xsn+jxc`, `ncn+ncn+xsn+jxc+jcs`, `ncn+ncn+xsn+jxt`, `ncn+ncn+xsv+ecc`, `ncn+ncn+xsv+etm`, `ncn+ncpa`, `ncn+ncpa+jca`, `ncn+ncpa+jca+jcm`, `ncn+ncpa+jca+jxc`, `ncn+ncpa+jca+jxt`, `ncn+ncpa+jcc`, `ncn+ncpa+jcj`, `ncn+ncpa+jcm`, `ncn+ncpa+jco`, `ncn+ncpa+jcr`, `ncn+ncpa+jcs`, `ncn+ncpa+jct`, `ncn+ncpa+jct+jcm`, `ncn+ncpa+jct+jxt`, `ncn+ncpa+jp+ecc`, `ncn+ncpa+jp+ecc+jxc`, `ncn+ncpa+jp+ecs`, `ncn+ncpa+jp+ecs+jxc`, `ncn+ncpa+jp+ef`, `ncn+ncpa+jp+ef+jcr`, `ncn+ncpa+jp+ef+jcr+jxc`, `ncn+ncpa+jp+ep+ef`, `ncn+ncpa+jp+ep+etm`, `ncn+ncpa+jp+ep+etn`, `ncn+ncpa+jp+etm`, `ncn+ncpa+jxc`, `ncn+ncpa+jxc+jca+jxc`, `ncn+ncpa+jxc+jco`, `ncn+ncpa+jxc+jcs`, `ncn+ncpa+jxt`, `ncn+ncpa+nbn+jcs`, `ncn+ncpa+ncn`, `ncn+ncpa+ncn+jca`, `ncn+ncpa+ncn+jca+jcm`, `ncn+ncpa+ncn+jca+jxc`, `ncn+ncpa+ncn+jca+jxt`, `ncn+ncpa+ncn+jcj`, `ncn+ncpa+ncn+jcm`, `ncn+ncpa+ncn+jco`, `ncn+ncpa+ncn+jcs`, `ncn+ncpa+ncn+jct`, `ncn+ncpa+ncn+jct+jcm`, `ncn+ncpa+ncn+jp+ef+jcr`, `ncn+ncpa+ncn+jp+ep+etm`, `ncn+ncpa+ncn+jxc`, `ncn+ncpa+ncn+jxt`, `ncn+ncpa+ncn+xsn+jcm`, `ncn+ncpa+ncn+xsn+jxt`, `ncn+ncpa+ncpa`, `ncn+ncpa+ncpa+jca`, `ncn+ncpa+ncpa+jcj`, `ncn+ncpa+ncpa+jcm`, `ncn+ncpa+ncpa+jco`, `ncn+ncpa+ncpa+jcs`, `ncn+ncpa+ncpa+jp+ep+ef`, `ncn+ncpa+ncpa+jxt`, `ncn+ncpa+ncpa+ncn`, `ncn+ncpa+xsn`, `ncn+ncpa+xsn+jcm`, `ncn+ncpa+xsn+jco`, `ncn+ncpa+xsn+jcs`, `ncn+ncpa+xsn+jp+ecc`, `ncn+ncpa+xsn+jp+etm`, `ncn+ncpa+xsn+jxt`, `ncn+ncpa+xsv+ecc`, `ncn+ncpa+xsv+ecs`, `ncn+ncpa+xsv+ecx`, `ncn+ncpa+xsv+ecx+px+etm`, `ncn+ncpa+xsv+ef`, `ncn+ncpa+xsv+ef+jcm`, `ncn+ncpa+xsv+ef+jcr`, `ncn+ncpa+xsv+etm`, _(truncated: full list in pipeline meta)_ | | **`morphologizer`** | `POS=CCONJ`, `POS=ADV`, `POS=SCONJ`, `POS=DET`, `POS=NOUN`, `POS=VERB`, `POS=ADJ`, `POS=PUNCT`, `POS=SPACE`, `POS=AUX`, `POS=PRON`, `POS=PROPN`, `POS=NUM`, `POS=INTJ`, `POS=PART`, `POS=X`, `POS=ADP`, `POS=SYM` | | **`parser`** | `ROOT`, `acl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `case`, `cc`, `ccomp`, `compound`, `conj`, `cop`, `csubj`, `dep`, `det`, `dislocated`, `fixed`, `flat`, `iobj`, `mark`, `nmod`, `nsubj`, `nummod`, `obj`, `obl`, `punct`, `xcomp` | | **`ner`** | `DT`, `LC`, `OG`, `PS`, `QT`, `TI` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 100.00 | | `TOKEN_P` | 100.00 | | `TOKEN_R` | 100.00 | | `TOKEN_F` | 100.00 | | `TAG_ACC` | 73.06 | | `POS_ACC` | 85.82 | | `SENTS_P` | 99.90 | | `SENTS_R` | 99.95 | | `SENTS_F` | 99.93 | | `DEP_UAS` | 73.61 | | `DEP_LAS` | 65.59 | | `LEMMA_ACC` | 83.57 | | `ENTS_P` | 77.04 | | `ENTS_R` | 66.03 | | `ENTS_F` | 71.11 |
Charlie911/vicuna-7b-v1.5-lora-timedial
Charlie911
2023-10-10T06:43:48Z
6
0
peft
[ "peft", "safetensors", "llama", "region:us" ]
null
2023-10-10T06:35:52Z
--- library_name: peft --- ## Training procedure The following `bitsandbytes` quantization config was used during training: - quant_method: bitsandbytes - load_in_8bit: True - load_in_4bit: False - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: fp4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float32 ### Framework versions - PEFT 0.5.0
spacy/mk_core_news_lg
spacy
2023-10-10T06:43:31Z
10
0
spacy
[ "spacy", "token-classification", "mk", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - mk license: cc-by-sa-4.0 model-index: - name: mk_core_news_lg results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7506382979 - name: NER Recall type: recall value: 0.7506382979 - name: NER F Score type: f_score value: 0.7506382979 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9309414621 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.6783968719 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.5298142717 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.6756756757 --- ### Details: https://spacy.io/models/mk#mk_core_news_lg Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer. | Feature | Description | | --- | --- | | **Name** | `mk_core_news_lg` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` | | **Components** | `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` | | **Vectors** | 274587 keys, 274587 unique vectors (300 dimensions) | | **Sources** | [Macedonian Corpus](https://blog.netcetera.com/macedonian-spacy-f3c85484777f) (Damjan Zlatinov, Melanija Gerasimovska, Borijan Georgievski, Marija Todosovska)<br />[spaCy lookups data](https://github.com/explosion/spacy-lookups-data) (Explosion)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (54 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `POS=PROPN`, `POS=AUX`, `POS=ADJ`, `POS=NOUN`, `POS=ADP`, `POS=PUNCT`, `POS=CONJ`, `POS=NUM`, `POS=VERB`, `POS=PRON`, `POS=ADV`, `POS=SCONJ`, `POS=PART`, `POS=SYM`, `_`, `POS=SPACE`, `POS=X`, `POS=INTJ` | | **`parser`** | `ROOT`, `advmod`, `att`, `aux`, `cc`, `dep`, `det`, `dobj`, `iobj`, `neg`, `nsubj`, `pobj`, `poss`, `pozm`, `pozv`, `prep`, `punct`, `relcl` | | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 100.00 | | `TOKEN_P` | 100.00 | | `TOKEN_R` | 100.00 | | `TOKEN_F` | 100.00 | | `SENTS_P` | 70.42 | | `SENTS_R` | 64.94 | | `SENTS_F` | 67.57 | | `DEP_UAS` | 67.84 | | `DEP_LAS` | 52.98 | | `ENTS_P` | 75.06 | | `ENTS_R` | 75.06 | | `ENTS_F` | 75.06 | | `POS_ACC` | 93.09 |
jiang9527li/Reinforce-cartpole
jiang9527li
2023-10-10T06:43:22Z
0
0
null
[ "CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class", "model-index", "region:us" ]
reinforcement-learning
2023-10-10T06:43:13Z
--- tags: - CartPole-v1 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Reinforce-cartpole results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics: - type: mean_reward value: 460.40 +/- 118.80 name: mean_reward verified: false --- # **Reinforce** Agent playing **CartPole-v1** This is a trained model of a **Reinforce** agent playing **CartPole-v1** . To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
spacy/mk_core_news_md
spacy
2023-10-10T06:43:02Z
3
0
spacy
[ "spacy", "token-classification", "mk", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - mk license: cc-by-sa-4.0 model-index: - name: mk_core_news_md results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7472245944 - name: NER Recall type: recall value: 0.7446808511 - name: NER F Score type: f_score value: 0.7459505541 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9260857837 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.6771344455 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.5201177625 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.7323943662 --- ### Details: https://spacy.io/models/mk#mk_core_news_md Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer. | Feature | Description | | --- | --- | | **Name** | `mk_core_news_md` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` | | **Components** | `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` | | **Vectors** | 274587 keys, 20000 unique vectors (300 dimensions) | | **Sources** | [Macedonian Corpus](https://blog.netcetera.com/macedonian-spacy-f3c85484777f) (Damjan Zlatinov, Melanija Gerasimovska, Borijan Georgievski, Marija Todosovska)<br />[spaCy lookups data](https://github.com/explosion/spacy-lookups-data) (Explosion)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (54 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `POS=PROPN`, `POS=AUX`, `POS=ADJ`, `POS=NOUN`, `POS=ADP`, `POS=PUNCT`, `POS=CONJ`, `POS=NUM`, `POS=VERB`, `POS=PRON`, `POS=ADV`, `POS=SCONJ`, `POS=PART`, `POS=SYM`, `_`, `POS=SPACE`, `POS=X`, `POS=INTJ` | | **`parser`** | `ROOT`, `advmod`, `att`, `aux`, `cc`, `dep`, `det`, `dobj`, `iobj`, `neg`, `nsubj`, `pobj`, `poss`, `pozm`, `pozv`, `prep`, `punct`, `relcl` | | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 100.00 | | `TOKEN_P` | 100.00 | | `TOKEN_R` | 100.00 | | `TOKEN_F` | 100.00 | | `SENTS_P` | 80.00 | | `SENTS_R` | 67.53 | | `SENTS_F` | 73.24 | | `DEP_UAS` | 67.71 | | `DEP_LAS` | 52.01 | | `ENTS_P` | 74.72 | | `ENTS_R` | 74.47 | | `ENTS_F` | 74.60 | | `POS_ACC` | 92.61 |
spacy/nb_core_news_md
spacy
2023-10-10T06:42:06Z
10
0
spacy
[ "spacy", "token-classification", "nb", "license:mit", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - nb license: mit model-index: - name: nb_core_news_md results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.811827957 - name: NER Recall type: recall value: 0.8050947867 - name: NER F Score type: f_score value: 0.8084473528 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9728910684 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9728910684 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9586576479 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.970965787 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8936788796 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8623767174 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9485952133 --- ### Details: https://spacy.io/models/nb#nb_core_news_md Norwegian (Bokmål) pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner, attribute_ruler. | Feature | Description | | --- | --- | | **Name** | `nb_core_news_md` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 500000 keys, 20000 unique vectors (300 dimensions) | | **Sources** | [UD Norwegian Bokmaal v2.8](https://github.com/UniversalDependencies/UD_Norwegian-Bokmaal) (Øvrelid, Lilja; Jørgensen, Fredrik; Hohle, Petter)<br />[NorNE: Norwegian Named Entities (commit: bd311de5)](https://github.com/ltgoslo/norne) (Language Technology Group (University of Oslo))<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `MIT` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (249 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=CCONJ`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=SCONJ`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Definite=Ind\|Gender=Neut\|Number=Plur\|POS=NOUN`, `POS=PUNCT`, `Mood=Ind\|POS=VERB\|Tense=Past\|VerbForm=Fin`, `POS=ADP`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Definite=Def\|Degree=Pos\|Number=Sing\|POS=ADJ`, `POS=PROPN`, `POS=X`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Definite=Def\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=PRON\|PronType=Rel`, `Mood=Ind\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Definite=Ind\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Number=Plur\|POS=ADJ\|VerbForm=Part`, `Definite=Ind\|Gender=Fem\|Number=Plur\|POS=NOUN`, `POS=ADV`, `Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Definite=Ind\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `POS=VERB\|VerbForm=Part`, `Definite=Ind\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Definite=Ind\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Degree=Pos\|Number=Plur\|POS=ADJ`, `NumType=Card\|Number=Plur\|POS=NUM`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Acc\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=PART`, `POS=VERB\|VerbForm=Inf`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|POS=AUX\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|POS=PROPN`, `POS=NOUN`, `Gender=Masc\|POS=PROPN`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Abbr=Yes\|POS=PROPN`, `POS=PART\|Polarity=Neg`, `Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Ind\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|POS=PROPN`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Definite=Def\|Degree=Sup\|POS=ADJ`, `Case=Gen\|Gender=Fem\|POS=PROPN`, `Number=Plur\|POS=DET\|PronType=Dem`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Definite=Ind\|Degree=Sup\|POS=ADJ`, `Definite=Def\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Gender=Neut\|POS=PROPN`, `Number=Plur\|POS=DET\|PronType=Int`, `Definite=Def\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Definite=Def\|POS=DET\|PronType=Dem`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Abbr=Yes\|Case=Gen\|POS=PROPN`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Degree=Cmp\|POS=ADJ`, `POS=ADJ\|VerbForm=Part`, `Gender=Neut\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Abbr=Yes\|POS=ADP`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Prs`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=NOUN`, `POS=AUX\|VerbForm=Part`, `POS=PRON\|PronType=Int`, `Gender=Fem\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Prs`, `Number=Plur\|POS=DET\|PronType=Ind`, `Degree=Pos\|POS=ADJ`, `Animacy=Hum\|Case=Nom\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `POS=VERB\|VerbForm=Inf\|Voice=Pass`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Ind`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Animacy=Hum\|Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Number=Plur\|POS=DET\|Polarity=Neg\|PronType=Neg`, `NumType=Card\|POS=NUM`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `POS=DET\|PronType=Prs`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Gen\|Gender=Neut\|POS=PROPN`, `Gender=Masc\|Number=Sing\|POS=DET\|Polarity=Neg\|PronType=Neg`, `Definite=Def\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Gender=Fem,Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `POS=AUX\|VerbForm=Inf`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Number=Plur\|POS=DET\|PronType=Tot`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Number=Plur\|POS=DET\|PronType=Prs`, `POS=SYM`, `Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Animacy=Hum\|Case=Nom\|Number=Sing\|POS=PRON\|PronType=Prs`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Prs`, `Case=Gen\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Abbr=Yes\|POS=ADV`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Definite=Def\|POS=DET\|PronType=Prs`, `Animacy=Hum\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Neut\|POS=NOUN`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int`, `Definite=Def\|NumType=Card\|POS=NUM`, `Mood=Imp\|POS=VERB\|VerbForm=Fin`, `Definite=Ind\|Number=Plur\|POS=NOUN`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Animacy=Hum\|Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Gender=Fem,Masc\|Number=Sing\|POS=PRON\|Person=3\|Polarity=Neg\|PronType=Neg,Prs`, `Number=Plur\|POS=PRON\|Person=3\|Polarity=Neg\|PronType=Neg,Prs`, `Definite=Def\|NumType=Card\|Number=Sing\|POS=NUM`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `POS=SPACE`, `Animacy=Hum\|Number=Sing\|POS=PRON\|PronType=Art,Prs`, `Mood=Imp\|POS=AUX\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=3\|PronType=Prs,Tot`, `Number=Plur\|POS=ADJ`, `Gender=Masc\|POS=NOUN`, `Abbr=Yes\|POS=NOUN`, `Case=Gen\|Definite=Ind\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Prs`, `POS=INTJ`, `Animacy=Hum\|Case=Nom\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Animacy=Hum\|Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=NOUN`, `POS=ADJ`, `Animacy=Hum\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Animacy=Hum\|Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Number=Sing\|POS=PRON\|Polarity=Neg\|PronType=Neg`, `Case=Gen\|POS=NOUN`, `Definite=Ind\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|POS=PROPN`, `Animacy=Hum\|Number=Plur\|POS=PRON\|PronType=Rcp`, `Case=Gen\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Fem,Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Prs`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Prs`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `NumType=Card\|Number=Sing\|POS=NUM`, `Animacy=Hum\|Case=Acc\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Animacy=Hum\|Case=Nom\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Gen\|Definite=Ind\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Degree=Sup\|POS=ADJ`, `Animacy=Hum\|POS=PRON\|PronType=Int`, `POS=DET\|PronType=Ind`, `Definite=Def\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Fem\|POS=NOUN`, `Case=Gen\|Number=Plur\|POS=DET\|PronType=Dem`, `Gender=Fem,Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs,Tot`, `Case=Gen\|Definite=Ind\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Gender=Neut\|Number=Sing\|POS=DET\|Polarity=Neg\|PronType=Neg`, `Number=Plur\|POS=NOUN`, `POS=PRON\|PronType=Prs`, `Case=Gen\|Definite=Ind\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Definite=Ind\|Number=Sing\|POS=VERB\|VerbForm=Part`, `Case=Gen\|Definite=Def\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Mood=Ind\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem,Ind`, `Animacy=Hum\|POS=PRON\|Poss=Yes\|PronType=Int`, `Abbr=Yes\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Abbr=Yes\|Definite=Def,Ind\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Rcp`, `Definite=Ind\|Degree=Pos\|POS=ADJ`, `Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|NumType=Card\|Number=Plur\|POS=NUM`, `Abbr=Yes\|Definite=Def,Ind\|Gender=Neut\|Number=Plur,Sing\|POS=NOUN`, `Case=Gen\|Number=Plur\|POS=DET\|PronType=Tot`, `Abbr=Yes\|Definite=Def,Ind\|Gender=Masc\|Number=Plur,Sing\|POS=NOUN`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Prs`, `Animacy=Hum\|Case=Gen,Nom\|Number=Sing\|POS=PRON\|PronType=Art,Prs`, `Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Case=Gen\|Number=Sing\|POS=PRON\|PronType=Art,Prs`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Definite=Ind\|Gender=Masc\|POS=NOUN`, `Definite=Def\|Number=Plur\|POS=NOUN`, `Number=Sing\|POS=ADJ\|VerbForm=Part`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Abbr=Yes\|Gender=Masc\|POS=NOUN`, `Abbr=Yes\|Case=Gen\|POS=NOUN`, `Abbr=Yes\|Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Abbr=Yes\|Degree=Pos\|POS=ADJ`, `Case=Gen\|Gender=Fem\|POS=NOUN`, `Case=Gen\|Degree=Cmp\|POS=ADJ`, `Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Gender=Masc\|Number=Sing\|POS=NOUN` | | **`parser`** | `ROOT`, `acl`, `acl:cleft`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `ccomp`, `compound`, `compound:prt`, `conj`, `cop`, `csubj`, `dep`, `det`, `discourse`, `expl`, `flat:foreign`, `flat:name`, `iobj`, `mark`, `nmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `orphan`, `parataxis`, `punct`, `xcomp` | | **`ner`** | `DRV`, `EVT`, `GPE_LOC`, `GPE_ORG`, `LOC`, `MISC`, `ORG`, `PER`, `PROD` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.81 | | `TOKEN_P` | 99.71 | | `TOKEN_R` | 99.53 | | `TOKEN_F` | 99.62 | | `POS_ACC` | 97.29 | | `MORPH_ACC` | 95.87 | | `MORPH_MICRO_P` | 97.59 | | `MORPH_MICRO_R` | 96.65 | | `MORPH_MICRO_F` | 97.12 | | `SENTS_P` | 95.12 | | `SENTS_R` | 94.60 | | `SENTS_F` | 94.86 | | `DEP_UAS` | 89.37 | | `DEP_LAS` | 86.24 | | `LEMMA_ACC` | 97.10 | | `TAG_ACC` | 97.29 | | `ENTS_P` | 81.18 | | `ENTS_R` | 80.51 | | `ENTS_F` | 80.84 |
spacy/nb_core_news_sm
spacy
2023-10-10T06:42:00Z
44
0
spacy
[ "spacy", "token-classification", "nb", "license:mit", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - nb license: mit model-index: - name: nb_core_news_sm results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7606060606 - name: NER Recall type: recall value: 0.7434834123 - name: NER F Score type: f_score value: 0.7519472738 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9673820215 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9673820215 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9531747234 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9689548785 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8841111858 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8516342729 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9271305064 --- ### Details: https://spacy.io/models/nb#nb_core_news_sm Norwegian (Bokmål) pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner, attribute_ruler. | Feature | Description | | --- | --- | | **Name** | `nb_core_news_sm` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | | **Sources** | [UD Norwegian Bokmaal v2.8](https://github.com/UniversalDependencies/UD_Norwegian-Bokmaal) (Øvrelid, Lilja; Jørgensen, Fredrik; Hohle, Petter)<br />[NorNE: Norwegian Named Entities (commit: bd311de5)](https://github.com/ltgoslo/norne) (Language Technology Group (University of Oslo)) | | **License** | `MIT` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (249 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=CCONJ`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=SCONJ`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Definite=Ind\|Gender=Neut\|Number=Plur\|POS=NOUN`, `POS=PUNCT`, `Mood=Ind\|POS=VERB\|Tense=Past\|VerbForm=Fin`, `POS=ADP`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Definite=Def\|Degree=Pos\|Number=Sing\|POS=ADJ`, `POS=PROPN`, `POS=X`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Definite=Def\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=PRON\|PronType=Rel`, `Mood=Ind\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Definite=Ind\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Number=Plur\|POS=ADJ\|VerbForm=Part`, `Definite=Ind\|Gender=Fem\|Number=Plur\|POS=NOUN`, `POS=ADV`, `Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Definite=Ind\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `POS=VERB\|VerbForm=Part`, `Definite=Ind\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Definite=Ind\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Degree=Pos\|Number=Plur\|POS=ADJ`, `NumType=Card\|Number=Plur\|POS=NUM`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Acc\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=PART`, `POS=VERB\|VerbForm=Inf`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|POS=AUX\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|POS=PROPN`, `POS=NOUN`, `Gender=Masc\|POS=PROPN`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Abbr=Yes\|POS=PROPN`, `POS=PART\|Polarity=Neg`, `Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Definite=Ind\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|POS=PROPN`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Definite=Def\|Degree=Sup\|POS=ADJ`, `Case=Gen\|Gender=Fem\|POS=PROPN`, `Number=Plur\|POS=DET\|PronType=Dem`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Definite=Ind\|Degree=Sup\|POS=ADJ`, `Definite=Def\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Gender=Neut\|POS=PROPN`, `Number=Plur\|POS=DET\|PronType=Int`, `Definite=Def\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Definite=Def\|POS=DET\|PronType=Dem`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Abbr=Yes\|Case=Gen\|POS=PROPN`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Degree=Cmp\|POS=ADJ`, `POS=ADJ\|VerbForm=Part`, `Gender=Neut\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Abbr=Yes\|POS=ADP`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Prs`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=NOUN`, `POS=AUX\|VerbForm=Part`, `POS=PRON\|PronType=Int`, `Gender=Fem\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Number=Plur\|POS=PRON\|Person=3\|PronType=Ind,Prs`, `Number=Plur\|POS=DET\|PronType=Ind`, `Degree=Pos\|POS=ADJ`, `Animacy=Hum\|Case=Nom\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `POS=VERB\|VerbForm=Inf\|Voice=Pass`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Ind`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Animacy=Hum\|Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Number=Plur\|POS=DET\|Polarity=Neg\|PronType=Neg`, `NumType=Card\|POS=NUM`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `POS=DET\|PronType=Prs`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Gen\|Gender=Neut\|POS=PROPN`, `Gender=Masc\|Number=Sing\|POS=DET\|Polarity=Neg\|PronType=Neg`, `Definite=Def\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Gender=Fem,Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `POS=AUX\|VerbForm=Inf`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Number=Plur\|POS=DET\|PronType=Tot`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Number=Plur\|POS=DET\|PronType=Prs`, `POS=SYM`, `Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Animacy=Hum\|Case=Nom\|Number=Sing\|POS=PRON\|PronType=Prs`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Prs`, `Case=Gen\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Abbr=Yes\|POS=ADV`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Definite=Def\|POS=DET\|PronType=Prs`, `Animacy=Hum\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Neut\|POS=NOUN`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int`, `Definite=Def\|NumType=Card\|POS=NUM`, `Mood=Imp\|POS=VERB\|VerbForm=Fin`, `Definite=Ind\|Number=Plur\|POS=NOUN`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Animacy=Hum\|Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Gender=Fem,Masc\|Number=Sing\|POS=PRON\|Person=3\|Polarity=Neg\|PronType=Neg,Prs`, `Number=Plur\|POS=PRON\|Person=3\|Polarity=Neg\|PronType=Neg,Prs`, `Definite=Def\|NumType=Card\|Number=Sing\|POS=NUM`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `POS=SPACE`, `Animacy=Hum\|Number=Sing\|POS=PRON\|PronType=Art,Prs`, `Mood=Imp\|POS=AUX\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=3\|PronType=Prs,Tot`, `Number=Plur\|POS=ADJ`, `Gender=Masc\|POS=NOUN`, `Abbr=Yes\|POS=NOUN`, `Case=Gen\|Definite=Ind\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Prs`, `POS=INTJ`, `Animacy=Hum\|Case=Nom\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Animacy=Hum\|Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Definite=Def\|Gender=Masc\|Number=Plur\|POS=NOUN`, `POS=ADJ`, `Animacy=Hum\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Animacy=Hum\|Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Number=Sing\|POS=PRON\|Polarity=Neg\|PronType=Neg`, `Case=Gen\|POS=NOUN`, `Definite=Ind\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|POS=PROPN`, `Animacy=Hum\|Number=Plur\|POS=PRON\|PronType=Rcp`, `Case=Gen\|Definite=Ind\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Fem,Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Ind,Prs`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Prs`, `Case=Gen\|Definite=Def\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Gen\|Definite=Def\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `NumType=Card\|Number=Sing\|POS=NUM`, `Animacy=Hum\|Case=Acc\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Animacy=Hum\|Case=Nom\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Gen\|Definite=Ind\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Degree=Sup\|POS=ADJ`, `Animacy=Hum\|POS=PRON\|PronType=Int`, `POS=DET\|PronType=Ind`, `Definite=Def\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Fem\|POS=NOUN`, `Case=Gen\|Number=Plur\|POS=DET\|PronType=Dem`, `Gender=Fem,Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs,Tot`, `Case=Gen\|Definite=Ind\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Gender=Neut\|Number=Sing\|POS=DET\|Polarity=Neg\|PronType=Neg`, `Number=Plur\|POS=NOUN`, `POS=PRON\|PronType=Prs`, `Case=Gen\|Definite=Ind\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Definite=Ind\|Number=Sing\|POS=VERB\|VerbForm=Part`, `Case=Gen\|Definite=Def\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Mood=Ind\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem,Ind`, `Animacy=Hum\|POS=PRON\|Poss=Yes\|PronType=Int`, `Abbr=Yes\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Abbr=Yes\|Definite=Def,Ind\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Rcp`, `Definite=Ind\|Degree=Pos\|POS=ADJ`, `Number=Plur\|POS=DET\|PronType=Art`, `Case=Gen\|NumType=Card\|Number=Plur\|POS=NUM`, `Abbr=Yes\|Definite=Def,Ind\|Gender=Neut\|Number=Plur,Sing\|POS=NOUN`, `Case=Gen\|Number=Plur\|POS=DET\|PronType=Tot`, `Abbr=Yes\|Definite=Def,Ind\|Gender=Masc\|Number=Plur,Sing\|POS=NOUN`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Gen\|Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Prs`, `Animacy=Hum\|Case=Gen,Nom\|Number=Sing\|POS=PRON\|PronType=Art,Prs`, `Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Case=Gen\|Number=Sing\|POS=PRON\|PronType=Art,Prs`, `Gender=Fem\|NumType=Card\|Number=Sing\|POS=NUM`, `Definite=Ind\|Gender=Masc\|POS=NOUN`, `Definite=Def\|Number=Plur\|POS=NOUN`, `Number=Sing\|POS=ADJ\|VerbForm=Part`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Abbr=Yes\|Gender=Masc\|POS=NOUN`, `Abbr=Yes\|Case=Gen\|POS=NOUN`, `Abbr=Yes\|Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Abbr=Yes\|Degree=Pos\|POS=ADJ`, `Case=Gen\|Gender=Fem\|POS=NOUN`, `Case=Gen\|Degree=Cmp\|POS=ADJ`, `Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Gender=Masc\|Number=Sing\|POS=NOUN` | | **`parser`** | `ROOT`, `acl`, `acl:cleft`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `ccomp`, `compound`, `compound:prt`, `conj`, `cop`, `csubj`, `dep`, `det`, `discourse`, `expl`, `flat:foreign`, `flat:name`, `iobj`, `mark`, `nmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `orphan`, `parataxis`, `punct`, `xcomp` | | **`ner`** | `DRV`, `EVT`, `GPE_LOC`, `GPE_ORG`, `LOC`, `MISC`, `ORG`, `PER`, `PROD` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.81 | | `TOKEN_P` | 99.71 | | `TOKEN_R` | 99.53 | | `TOKEN_F` | 99.62 | | `POS_ACC` | 96.74 | | `MORPH_ACC` | 95.32 | | `MORPH_MICRO_P` | 97.02 | | `MORPH_MICRO_R` | 96.07 | | `MORPH_MICRO_F` | 96.54 | | `SENTS_P` | 91.96 | | `SENTS_R` | 93.48 | | `SENTS_F` | 92.71 | | `DEP_UAS` | 88.41 | | `DEP_LAS` | 85.16 | | `LEMMA_ACC` | 96.90 | | `TAG_ACC` | 96.74 | | `ENTS_P` | 76.06 | | `ENTS_R` | 74.35 | | `ENTS_F` | 75.19 |
spacy/nl_core_news_sm
spacy
2023-10-10T06:41:07Z
101
0
spacy
[ "spacy", "token-classification", "nl", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - nl license: cc-by-sa-4.0 model-index: - name: nl_core_news_sm results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7496350365 - name: NER Recall type: recall value: 0.7102351314 - name: NER F Score type: f_score value: 0.7294034091 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.939195673 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9572746505 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9504635184 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9504328674 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8535422689 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.80149091 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.8658922914 --- ### Details: https://spacy.io/models/nl#nl_core_news_sm Dutch pipeline optimized for CPU. Components: tok2vec, morphologizer, tagger, parser, lemmatizer (trainable_lemmatizer), senter, ner. | Feature | Description | | --- | --- | | **Name** | `nl_core_news_sm` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | | **Sources** | [UD Dutch LassySmall v2.8](https://github.com/UniversalDependencies/UD_Dutch-LassySmall) (Bouma, Gosse; van Noord, Gertjan)<br />[Dutch NER Annotations for UD LassySmall](https://nlp.town) (NLP Town)<br />[UD Dutch Alpino v2.8](https://github.com/UniversalDependencies/UD_Dutch-Alpino) (Zeman, Daniel; Žabokrtský, Zdeněk; Bouma, Gosse; van Noord, Gertjan) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (323 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `POS=PRON\|Person=3\|PronType=Dem`, `Number=Sing\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `POS=ADV`, `POS=VERB\|VerbForm=Part`, `POS=PUNCT`, `Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Fin`, `POS=ADP`, `POS=NUM`, `Number=Plur\|POS=NOUN`, `POS=VERB\|VerbForm=Inf`, `POS=SCONJ`, `Definite=Def\|POS=DET`, `Gender=Com\|Number=Sing\|POS=NOUN`, `Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Degree=Pos\|POS=ADJ`, `Gender=Neut\|Number=Sing\|POS=PROPN`, `Gender=Com\|Number=Sing\|POS=PROPN`, `POS=AUX\|VerbForm=Inf`, `Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin`, `POS=DET`, `Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=PRON\|Person=3\|PronType=Prs`, `POS=CCONJ`, `Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `POS=PRON\|Person=3\|PronType=Ind`, `Degree=Cmp\|POS=ADJ`, `Case=Nom\|POS=PRON\|Person=1\|PronType=Prs`, `Definite=Ind\|POS=DET`, `Case=Nom\|POS=PRON\|Person=3\|PronType=Prs`, `POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Number=Plur\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `POS=PRON\|PronType=Rel`, `Case=Acc\|POS=PRON\|Person=1\|PronType=Prs`, `Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin`, `Gender=Com,Neut\|Number=Sing\|POS=NOUN`, `Case=Acc\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|POS=PRON\|Person=3\|PronType=Prs`, `POS=PROPN`, `POS=PRON\|PronType=Ind`, `POS=PRON\|Person=3\|PronType=Int`, `Case=Acc\|POS=PRON\|PronType=Rcp`, `Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Fin`, `Number=Sing\|POS=NOUN`, `POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `POS=SYM`, `Abbr=Yes\|POS=X`, `Gender=Com,Neut\|Number=Sing\|POS=PROPN`, `Degree=Sup\|POS=ADJ`, `POS=ADJ`, `Number=Sing\|POS=PROPN`, `POS=PRON\|PronType=Dem`, `POS=AUX\|VerbForm=Part`, `POS=SPACE`, `POS=PRON\|Person=3\|PronType=Rel`, `Number=Plur\|POS=PROPN`, `POS=PRON\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Dat\|POS=PRON\|PronType=Dem`, `Case=Nom\|POS=PRON\|Person=2\|PronType=Prs`, `POS=INTJ`, `Case=Acc\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Gen\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=PRON\|PronType=Int`, `POS=PRON\|Person=2\|PronType=Prs`, `POS=PRON\|Person=3`, `Case=Gen\|POS=PRON\|Person=2\|PronType=Prs`, `POS=X` | | **`tagger`** | `ADJ\|nom\|basis\|met-e\|mv-n`, `ADJ\|nom\|basis\|met-e\|zonder-n\|bijz`, `ADJ\|nom\|basis\|met-e\|zonder-n\|stan`, `ADJ\|nom\|basis\|zonder\|mv-n`, `ADJ\|nom\|basis\|zonder\|zonder-n`, `ADJ\|nom\|comp\|met-e\|mv-n`, `ADJ\|nom\|comp\|met-e\|zonder-n\|stan`, `ADJ\|nom\|sup\|met-e\|mv-n`, `ADJ\|nom\|sup\|met-e\|zonder-n\|bijz`, `ADJ\|nom\|sup\|met-e\|zonder-n\|stan`, `ADJ\|nom\|sup\|zonder\|zonder-n`, `ADJ\|postnom\|basis\|met-s`, `ADJ\|postnom\|basis\|zonder`, `ADJ\|postnom\|comp\|met-s`, `ADJ\|prenom\|basis\|met-e\|bijz`, `ADJ\|prenom\|basis\|met-e\|stan`, `ADJ\|prenom\|basis\|zonder`, `ADJ\|prenom\|comp\|met-e\|stan`, `ADJ\|prenom\|comp\|zonder`, `ADJ\|prenom\|sup\|met-e\|stan`, `ADJ\|prenom\|sup\|zonder`, `ADJ\|vrij\|basis\|zonder`, `ADJ\|vrij\|comp\|zonder`, `ADJ\|vrij\|dim\|zonder`, `ADJ\|vrij\|sup\|zonder`, `BW`, `LET`, `LID\|bep\|dat\|evmo`, `LID\|bep\|gen\|evmo`, `LID\|bep\|gen\|rest3`, `LID\|bep\|stan\|evon`, `LID\|bep\|stan\|rest`, `LID\|onbep\|stan\|agr`, `N\|eigen\|ev\|basis\|gen`, `N\|eigen\|ev\|basis\|genus\|stan`, `N\|eigen\|ev\|basis\|onz\|stan`, `N\|eigen\|ev\|basis\|zijd\|stan`, `N\|eigen\|ev\|dim\|onz\|stan`, `N\|eigen\|mv\|basis`, `N\|soort\|ev\|basis\|dat`, `N\|soort\|ev\|basis\|gen`, `N\|soort\|ev\|basis\|genus\|stan`, `N\|soort\|ev\|basis\|onz\|stan`, `N\|soort\|ev\|basis\|zijd\|stan`, `N\|soort\|ev\|dim\|onz\|stan`, `N\|soort\|mv\|basis`, `N\|soort\|mv\|dim`, `SPEC\|afgebr`, `SPEC\|afk`, `SPEC\|deeleigen`, `SPEC\|enof`, `SPEC\|meta`, `SPEC\|symb`, `SPEC\|vreemd`, `TSW`, `TW\|hoofd\|nom\|mv-n\|basis`, `TW\|hoofd\|nom\|mv-n\|dim`, `TW\|hoofd\|nom\|zonder-n\|basis`, `TW\|hoofd\|nom\|zonder-n\|dim`, `TW\|hoofd\|prenom\|stan`, `TW\|hoofd\|vrij`, `TW\|rang\|nom\|mv-n`, `TW\|rang\|nom\|zonder-n`, `TW\|rang\|prenom\|stan`, `VG\|neven`, `VG\|onder`, `VNW\|aanw\|adv-pron\|obl\|vol\|3o\|getal`, `VNW\|aanw\|adv-pron\|stan\|red\|3\|getal`, `VNW\|aanw\|det\|dat\|nom\|met-e\|zonder-n`, `VNW\|aanw\|det\|dat\|prenom\|met-e\|evmo`, `VNW\|aanw\|det\|gen\|prenom\|met-e\|rest3`, `VNW\|aanw\|det\|stan\|nom\|met-e\|mv-n`, `VNW\|aanw\|det\|stan\|nom\|met-e\|zonder-n`, `VNW\|aanw\|det\|stan\|prenom\|met-e\|rest`, `VNW\|aanw\|det\|stan\|prenom\|zonder\|agr`, `VNW\|aanw\|det\|stan\|prenom\|zonder\|evon`, `VNW\|aanw\|det\|stan\|prenom\|zonder\|rest`, `VNW\|aanw\|det\|stan\|vrij\|zonder`, `VNW\|aanw\|pron\|gen\|vol\|3m\|ev`, `VNW\|aanw\|pron\|stan\|vol\|3o\|ev`, `VNW\|aanw\|pron\|stan\|vol\|3\|getal`, `VNW\|betr\|det\|stan\|nom\|met-e\|zonder-n`, `VNW\|betr\|det\|stan\|nom\|zonder\|zonder-n`, `VNW\|betr\|pron\|stan\|vol\|3\|ev`, `VNW\|betr\|pron\|stan\|vol\|persoon\|getal`, `VNW\|bez\|det\|gen\|vol\|3\|ev\|prenom\|met-e\|rest3`, `VNW\|bez\|det\|stan\|nadr\|2v\|mv\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|red\|1\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|red\|2v\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|red\|3\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|1\|ev\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|1\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|1\|mv\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|1\|mv\|prenom\|zonder\|evon`, `VNW\|bez\|det\|stan\|vol\|2v\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|2\|getal\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|3m\|ev\|nom\|met-e\|zonder-n`, `VNW\|bez\|det\|stan\|vol\|3m\|ev\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|3p\|mv\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|3v\|ev\|nom\|met-e\|zonder-n`, `VNW\|bez\|det\|stan\|vol\|3v\|ev\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|3\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|3\|mv\|prenom\|zonder\|agr`, `VNW\|excl\|pron\|stan\|vol\|3\|getal`, `VNW\|onbep\|adv-pron\|gen\|red\|3\|getal`, `VNW\|onbep\|adv-pron\|obl\|vol\|3o\|getal`, `VNW\|onbep\|det\|stan\|nom\|met-e\|mv-n`, `VNW\|onbep\|det\|stan\|nom\|met-e\|zonder-n`, `VNW\|onbep\|det\|stan\|nom\|zonder\|zonder-n`, `VNW\|onbep\|det\|stan\|prenom\|met-e\|agr`, `VNW\|onbep\|det\|stan\|prenom\|met-e\|evz`, `VNW\|onbep\|det\|stan\|prenom\|met-e\|mv`, `VNW\|onbep\|det\|stan\|prenom\|met-e\|rest`, `VNW\|onbep\|det\|stan\|prenom\|zonder\|agr`, `VNW\|onbep\|det\|stan\|prenom\|zonder\|evon`, `VNW\|onbep\|det\|stan\|vrij\|zonder`, `VNW\|onbep\|grad\|gen\|nom\|met-e\|mv-n\|basis`, `VNW\|onbep\|grad\|stan\|nom\|met-e\|mv-n\|basis`, `VNW\|onbep\|grad\|stan\|nom\|met-e\|mv-n\|sup`, `VNW\|onbep\|grad\|stan\|nom\|met-e\|zonder-n\|basis`, `VNW\|onbep\|grad\|stan\|nom\|met-e\|zonder-n\|sup`, `VNW\|onbep\|grad\|stan\|prenom\|met-e\|agr\|basis`, `VNW\|onbep\|grad\|stan\|prenom\|met-e\|agr\|comp`, `VNW\|onbep\|grad\|stan\|prenom\|met-e\|agr\|sup`, `VNW\|onbep\|grad\|stan\|prenom\|met-e\|mv\|basis`, `VNW\|onbep\|grad\|stan\|prenom\|zonder\|agr\|basis`, `VNW\|onbep\|grad\|stan\|prenom\|zonder\|agr\|comp`, `VNW\|onbep\|grad\|stan\|vrij\|zonder\|basis`, `VNW\|onbep\|grad\|stan\|vrij\|zonder\|comp`, `VNW\|onbep\|grad\|stan\|vrij\|zonder\|sup`, `VNW\|onbep\|pron\|gen\|vol\|3p\|ev`, `VNW\|onbep\|pron\|stan\|vol\|3o\|ev`, `VNW\|onbep\|pron\|stan\|vol\|3p\|ev`, `VNW\|pers\|pron\|gen\|vol\|2\|getal`, `VNW\|pers\|pron\|nomin\|nadr\|3m\|ev\|masc`, `VNW\|pers\|pron\|nomin\|nadr\|3v\|ev\|fem`, `VNW\|pers\|pron\|nomin\|red\|1\|mv`, `VNW\|pers\|pron\|nomin\|red\|2v\|ev`, `VNW\|pers\|pron\|nomin\|red\|2\|getal`, `VNW\|pers\|pron\|nomin\|red\|3p\|ev\|masc`, `VNW\|pers\|pron\|nomin\|red\|3\|ev\|masc`, `VNW\|pers\|pron\|nomin\|vol\|1\|ev`, `VNW\|pers\|pron\|nomin\|vol\|1\|mv`, `VNW\|pers\|pron\|nomin\|vol\|2b\|getal`, `VNW\|pers\|pron\|nomin\|vol\|2v\|ev`, `VNW\|pers\|pron\|nomin\|vol\|2\|getal`, `VNW\|pers\|pron\|nomin\|vol\|3p\|mv`, `VNW\|pers\|pron\|nomin\|vol\|3v\|ev\|fem`, `VNW\|pers\|pron\|nomin\|vol\|3\|ev\|masc`, `VNW\|pers\|pron\|obl\|nadr\|3m\|ev\|masc`, `VNW\|pers\|pron\|obl\|red\|3\|ev\|masc`, `VNW\|pers\|pron\|obl\|vol\|2v\|ev`, `VNW\|pers\|pron\|obl\|vol\|3p\|mv`, `VNW\|pers\|pron\|obl\|vol\|3\|ev\|masc`, `VNW\|pers\|pron\|obl\|vol\|3\|getal\|fem`, `VNW\|pers\|pron\|stan\|nadr\|2v\|mv`, `VNW\|pers\|pron\|stan\|red\|3\|ev\|fem`, `VNW\|pers\|pron\|stan\|red\|3\|ev\|onz`, `VNW\|pers\|pron\|stan\|red\|3\|mv`, `VNW\|pr\|pron\|obl\|nadr\|1\|ev`, `VNW\|pr\|pron\|obl\|nadr\|2v\|getal`, `VNW\|pr\|pron\|obl\|nadr\|2\|getal`, `VNW\|pr\|pron\|obl\|red\|1\|ev`, `VNW\|pr\|pron\|obl\|red\|2v\|getal`, `VNW\|pr\|pron\|obl\|vol\|1\|ev`, `VNW\|pr\|pron\|obl\|vol\|1\|mv`, `VNW\|pr\|pron\|obl\|vol\|2\|getal`, `VNW\|recip\|pron\|gen\|vol\|persoon\|mv`, `VNW\|recip\|pron\|obl\|vol\|persoon\|mv`, `VNW\|refl\|pron\|obl\|nadr\|3\|getal`, `VNW\|refl\|pron\|obl\|red\|3\|getal`, `VNW\|vb\|adv-pron\|obl\|vol\|3o\|getal`, `VNW\|vb\|det\|stan\|nom\|met-e\|zonder-n`, `VNW\|vb\|det\|stan\|prenom\|met-e\|rest`, `VNW\|vb\|det\|stan\|prenom\|zonder\|evon`, `VNW\|vb\|pron\|gen\|vol\|3m\|ev`, `VNW\|vb\|pron\|gen\|vol\|3p\|mv`, `VNW\|vb\|pron\|gen\|vol\|3v\|ev`, `VNW\|vb\|pron\|stan\|vol\|3o\|ev`, `VNW\|vb\|pron\|stan\|vol\|3p\|getal`, `VZ\|fin`, `VZ\|init`, `VZ\|versm`, `WW\|inf\|nom\|zonder\|zonder-n`, `WW\|inf\|prenom\|met-e`, `WW\|inf\|vrij\|zonder`, `WW\|od\|nom\|met-e\|mv-n`, `WW\|od\|nom\|met-e\|zonder-n`, `WW\|od\|prenom\|met-e`, `WW\|od\|prenom\|zonder`, `WW\|od\|vrij\|zonder`, `WW\|pv\|conj\|ev`, `WW\|pv\|tgw\|ev`, `WW\|pv\|tgw\|met-t`, `WW\|pv\|tgw\|mv`, `WW\|pv\|verl\|ev`, `WW\|pv\|verl\|mv`, `WW\|vd\|nom\|met-e\|mv-n`, `WW\|vd\|nom\|met-e\|zonder-n`, `WW\|vd\|prenom\|met-e`, `WW\|vd\|prenom\|zonder`, `WW\|vd\|vrij\|zonder`, `_SP` | | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `ccomp`, `compound:prt`, `conj`, `cop`, `csubj`, `dep`, `det`, `expl`, `expl:pv`, `fixed`, `flat`, `iobj`, `mark`, `nmod`, `nmod:poss`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `obl:agent`, `orphan`, `parataxis`, `punct`, `xcomp` | | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` | </details> ### Accuracy | Type | Score | | --- | --- | | `TAG_ACC` | 93.92 | | `SENTS_P` | 85.00 | | `SENTS_R` | 88.24 | | `SENTS_F` | 86.59 | | `DEP_UAS` | 85.35 | | `DEP_LAS` | 80.15 | | `ENTS_P` | 74.96 | | `ENTS_R` | 71.02 | | `ENTS_F` | 72.94 | | `TOKEN_ACC` | 99.94 | | `TOKEN_P` | 99.74 | | `TOKEN_R` | 99.76 | | `TOKEN_F` | 99.75 | | `POS_ACC` | 95.73 | | `MORPH_ACC` | 95.05 | | `MORPH_MICRO_P` | 95.82 | | `MORPH_MICRO_R` | 93.63 | | `MORPH_MICRO_F` | 94.71 | | `LEMMA_ACC` | 95.04 |
spacy/pl_core_news_lg
spacy
2023-10-10T06:41:03Z
21
3
spacy
[ "spacy", "token-classification", "pl", "license:gpl-3.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - pl license: gpl-3.0 model-index: - name: pl_core_news_lg results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.847446671 - name: NER Recall type: recall value: 0.8355640535 - name: NER F Score type: f_score value: 0.8414634146 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9828973843 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9781017658 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9098299967 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9424670256 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.894969847 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8237918475 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9631305135 --- ### Details: https://spacy.io/models/pl#pl_core_news_lg Polish pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, lemmatizer (trainable_lemmatizer), tagger, senter, ner. | Feature | Description | | --- | --- | | **Name** | `pl_core_news_lg` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `tagger`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `tagger`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) | | **Sources** | [UD Polish PDB v2.8](https://github.com/UniversalDependencies/UD_Polish-PDB/) (Wróblewska, Alina; Zeman, Daniel; Mašek, Jan; Rosa, Rudolf)<br />[National Corpus of Polish](http://nkjp.pl/) (Mirosław Bańko, Rafał L. Górski, Barbara Lewandowska-Tomaszczyk, Marek Łaziński, Piotr Pęzik, Adam Przepiórkowski)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `GNU GPL 3.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (1726 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `AdpType=Prep\|POS=ADP\|Variant=Short`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `POS=CCONJ`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=PUNCT\|PunctType=Peri`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `POS=PUNCT\|PunctType=Comm`, `Animacy=Inan\|Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Ins\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=NOUN`, `AdpType=Prep\|POS=ADP`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Aspect=Imp\|POS=VERB\|Tense=Pres\|VerbForm=Conv\|Voice=Act`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `POS=ADV`, `Animacy=Hum\|Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Ins\|Gender=Neut\|NumType=Sets\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Fem\|NumForm=Word\|Number=Plur\|POS=NUM`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Nhum\|Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Gen\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Case=Ins\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Ins\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Animacy=Hum\|Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Inan\|Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Case=Gen\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Animacy=Nhum\|Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Loc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Loc\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Neut\|Number=Ptan\|POS=NOUN`, `AdpType=Prep\|POS=ADP\|Variant=Long`, `Animacy=Inan\|Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Ins\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Animacy=Hum\|Aspect=Imp\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Nhum\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Ins\|Gender=Neut\|NumType=Sets\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Neut\|NumType=Sets\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Loc\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Aspect=Imp\|Case=Nom\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Aspect=Perf\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Nhum\|Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|NumType=Sets\|Number=Plur\|POS=NOUN`, `Aspect=Perf\|Case=Gen\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `POS=SPACE`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Case=Nom\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Ins\|Gender=Neut\|Number=Ptan\|POS=NOUN`, `Case=Ins\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Animacy=Nhum\|Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Nhum\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Neut\|NumForm=Word\|NumType=Sets\|Number=Plur\|POS=NUM`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `POS=PART`, `Aspect=Perf\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Degree=Pos\|POS=ADV`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Case=Gen\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `POS=SCONJ`, `Case=Dat\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|NumType=Sets\|Number=Sing\|POS=NOUN`, `Animacy=Hum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Loc\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Ins\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Nhum\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Neut\|NumType=Sets\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Aspect=Perf\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Nhum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Animacy=Hum\|Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Hyph=Yes\|POS=ADJ`, `POS=PUNCT\|PunctType=Dash`, `Animacy=Inan\|Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Perf\|Case=Ins\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Perf\|Case=Gen\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Nhum\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Ins\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Aspect=Imp\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Loc\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Aspect=Perf\|Case=Ins\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Inan\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `POS=ADV\|PronType=Rel`, `Animacy=Hum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Inan\|Aspect=Perf\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Aspect=Imp\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Aspect=Perf\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Animacy=Nhum\|Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Ins\|Gender=Fem\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Hum\|Case=Dat\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Degree=Cmp\|POS=ADV`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Aspect=Perf\|Case=Loc\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Case=Nom\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Hum\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Animacy=Hum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Ins\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Nhum\|Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Nhum\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Animacy=Nhum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Aspect=Perf\|Gender=Neut\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Hum\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Aspect=Imp\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Nhum\|Case=Ins\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Nhum\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Animacy=Nhum\|Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Nhum\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Gen\|Gender=Neut\|Number=Ptan\|POS=NOUN`, `Aspect=Imp\|Case=Ins\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Inan\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Aspect=Perf\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|Number=Ptan\|POS=NOUN`, `Aspect=Imp\|Case=Nom\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Ind`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Aspect=Imp\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Hum\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Dat\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Aspect=Imp\|Case=Acc\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `POS=ADV\|PronType=Dem`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Ind`, `Animacy=Nhum\|Aspect=Perf\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Inan\|Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Aspect=Perf\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Hum\|Case=Ins\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Loc\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Neut\|NumType=Sets\|Number=Plur\|POS=NOUN`, `Case=Loc\|Gender=Fem\|NumForm=Word\|Number=Plur\|POS=NUM`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Loc\|Gender=Neut\|NumType=Sets\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Inan\|Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Ptan\|POS=PRON\|PronType=Tot`, `Animacy=Nhum\|Aspect=Perf\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Aspect=Perf\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Nhum\|Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|NumType=Sets\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Aspect=Perf\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Inan\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Fem\|NumForm=Word\|Number=Plur\|POS=NUM`, `Degree=Pos\|POS=ADV\|PronType=Dem`, `Aspect=Imp\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Nhum\|Case=Acc\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Aspect=Perf\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Nom\|Gender=Neut\|Number=Ptan\|POS=NOUN`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Inan\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Rel`, `Animacy=Nhum\|Aspect=Imp\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Aspect=Imp\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Loc\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Dat\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Rel`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Neut\|NumType=Sets\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Aspect=Perf\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Rel`, `Animacy=Nhum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Nhum\|Aspect=Perf\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Rel`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Rel`, `Case=Dat\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Aspect=Imp\|Case=Dat\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Gender=Neut\|NumForm=Word\|Number=Plur\|POS=NUM`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Case=Nom\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Aspect=Imp\|Case=Gen\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Aspect=Imp\|Case=Ins\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Loc\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `ConjType=Comp\|POS=SCONJ`, `Animacy=Inan\|Aspect=Imp\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Loc\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Aspect=Imp\|Case=Dat\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Animacy=Inan\|Aspect=Imp\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Nom\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|VerbType=Quasi`, `Animacy=Hum\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `POS=ADJ\|PrepCase=Pre`, `Animacy=Inan\|Aspect=Perf\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Animacy=Nhum\|Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Ins\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Aspect=Perf\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Acc\|Gender=Neut\|NumType=Sets\|Number=Plur\|POS=NOUN`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Case=Ins\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Hum\|Aspect=Perf\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Neut\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Hum\|Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Tot`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Aspect=Imp\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Animacy=Hum\|Aspect=Imp\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Aspect=Perf\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Hum\|Aspect=Imp,Perf\|Clitic=Yes\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|Variant=Long\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `POS=PUNCT\|PunctType=Excl`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Gender=Neut\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Aspect=Perf\|POS=VERB\|Tense=Past\|VerbForm=Conv\|Voice=Act`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Aspect=Imp\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Foreign=Yes\|POS=X`, `POS=PART\|Polarity=Neg`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Aspect=Imp\|Gender=Neut\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Aspect=Imp\|Clitic=Yes\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|Variant=Short\|VerbForm=Fin\|Voice=Act`, `Animacy=Hum\|Aspect=Imp,Perf\|Clitic=Yes\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Past\|Variant=Long\|VerbForm=Fin\|Voice=Act`, `Degree=Pos\|POS=ADV\|PronType=Int`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Neg`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Int`, `POS=PUNCT\|PunctType=Qest`, `Animacy=Inan\|Case=Nom\|Degree=Pos\|Gender=Masc\|NumForm=Roman\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Animacy=Hum\|Aspect=Imp,Perf\|Clitic=Yes\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|Variant=Short\|VerbForm=Fin\|Voice=Act`, `Aspect=Imp\|Case=Loc\|Gender=Neut\|Number=Sing\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `POS=ADV\|PronType=Int`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs\|Variant=Short`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Tot`, `Animacy=Hum\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Aspect=Imp\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Inan\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Loc\|Gender=Neut\|Number=Ptan\|POS=PROPN`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Int`, `POS=ADV\|PronType=Neg`, `Animacy=Hum\|Aspect=Imp\|Clitic=Yes\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|Variant=Long\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Neg`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Int`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Animacy=Hum\|Aspect=Perf\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Animacy=Hum\|Case=Acc\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Dat\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Aspect=Imp\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|VerbType=Mod\|Voice=Act`, `POS=PART\|PartType=Int`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `POS=ADV\|PronType=Ind`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Animacy=Hum\|Aspect=Perf\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Aspect=Imp\|Clitic=Yes\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|Variant=Short\|VerbForm=Fin\|Voice=Act`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Acc\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|POS=VERB\|Person=0\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|NumForm=Digit\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Aspect=Perf\|Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs\|Variant=Short`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Loc\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Neg`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `POS=PART\|PartType=Mod`, `Aspect=Imp\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|POS=AUX\|VerbForm=Inf\|Voice=Act`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Neg`, _(truncated: full list in pipeline meta)_ | | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advcl:cmpr`, `advcl:relcl`, `advmod`, `advmod:arg`, `advmod:emph`, `advmod:neg`, `amod`, `amod:flat`, `appos`, `aux`, `aux:cnd`, `aux:imp`, `aux:pass`, `case`, `cc`, `cc:preconj`, `ccomp`, `ccomp:cleft`, `ccomp:obj`, `conj`, `cop`, `csubj`, `dep`, `det`, `det:numgov`, `det:nummod`, `det:poss`, `discourse:intj`, `expl:pv`, `fixed`, `flat`, `flat:foreign`, `iobj`, `list`, `mark`, `nmod`, `nmod:arg`, `nmod:flat`, `nmod:poss`, `nsubj`, `nsubj:pass`, `nummod`, `nummod:gov`, `obj`, `obl`, `obl:agent`, `obl:arg`, `obl:cmpr`, `orphan`, `parataxis:insert`, `parataxis:obj`, `punct`, `vocative`, `xcomp`, `xcomp:cleft`, `xcomp:pred` | | **`tagger`** | `ADJ`, `ADJA`, `ADJC`, `ADJP`, `ADV`, `AGLT`, `BEDZIE`, `BREV`, `BURK`, `COMP`, `CONJ`, `DEPR`, `FIN`, `GER`, `IMPS`, `IMPT`, `INF`, `INTERJ`, `INTERP`, `NUM`, `NUMCOL`, `PACT`, `PANT`, `PCON`, `PPAS`, `PPRON12`, `PPRON3`, `PRAET`, `PRED`, `PREP`, `QUB`, `SIEBIE`, `SUBST`, `WINIEN`, `XXX`, `_SP` | | **`ner`** | `date`, `geogName`, `orgName`, `persName`, `placeName`, `time` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.98 | | `TOKEN_P` | 99.63 | | `TOKEN_R` | 99.83 | | `TOKEN_F` | 99.73 | | `POS_ACC` | 97.81 | | `MORPH_ACC` | 90.98 | | `MORPH_MICRO_P` | 95.74 | | `MORPH_MICRO_R` | 95.61 | | `MORPH_MICRO_F` | 95.67 | | `SENTS_P` | 96.51 | | `SENTS_R` | 96.12 | | `SENTS_F` | 96.31 | | `DEP_UAS` | 89.50 | | `DEP_LAS` | 82.38 | | `LEMMA_ACC` | 94.25 | | `TAG_ACC` | 98.29 | | `ENTS_P` | 84.74 | | `ENTS_R` | 83.56 | | `ENTS_F` | 84.15 |
spacy/pl_core_news_sm
spacy
2023-10-10T06:40:09Z
15
0
spacy
[ "spacy", "token-classification", "pl", "license:gpl-3.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - pl license: gpl-3.0 model-index: - name: pl_core_news_sm results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8019169329 - name: NER Recall type: recall value: 0.7998725303 - name: NER F Score type: f_score value: 0.8008934269 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9793610146 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9705532162 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.8796817839 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9309169 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8774553377 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.7968842575 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9606868504 --- ### Details: https://spacy.io/models/pl#pl_core_news_sm Polish pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, lemmatizer (trainable_lemmatizer), tagger, senter, ner. | Feature | Description | | --- | --- | | **Name** | `pl_core_news_sm` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `tagger`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `tagger`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | | **Sources** | [UD Polish PDB v2.8](https://github.com/UniversalDependencies/UD_Polish-PDB/) (Wróblewska, Alina; Zeman, Daniel; Mašek, Jan; Rosa, Rudolf)<br />[National Corpus of Polish](http://nkjp.pl/) (Mirosław Bańko, Rafał L. Górski, Barbara Lewandowska-Tomaszczyk, Marek Łaziński, Piotr Pęzik, Adam Przepiórkowski) | | **License** | `GNU GPL 3.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (1726 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `AdpType=Prep\|POS=ADP\|Variant=Short`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `POS=CCONJ`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=PUNCT\|PunctType=Peri`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `POS=PUNCT\|PunctType=Comm`, `Animacy=Inan\|Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Ins\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=NOUN`, `AdpType=Prep\|POS=ADP`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Aspect=Imp\|POS=VERB\|Tense=Pres\|VerbForm=Conv\|Voice=Act`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `POS=ADV`, `Animacy=Hum\|Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Ins\|Gender=Neut\|NumType=Sets\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Fem\|NumForm=Word\|Number=Plur\|POS=NUM`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Nhum\|Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Gen\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Case=Ins\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Ins\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Animacy=Hum\|Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Inan\|Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Case=Gen\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Animacy=Nhum\|Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Loc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Loc\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Neut\|Number=Ptan\|POS=NOUN`, `AdpType=Prep\|POS=ADP\|Variant=Long`, `Animacy=Inan\|Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Ins\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Animacy=Hum\|Aspect=Imp\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Nhum\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Ins\|Gender=Neut\|NumType=Sets\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Neut\|NumType=Sets\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Loc\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Aspect=Imp\|Case=Nom\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Aspect=Perf\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Nhum\|Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|NumType=Sets\|Number=Plur\|POS=NOUN`, `Aspect=Perf\|Case=Gen\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `POS=SPACE`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Case=Nom\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Ins\|Gender=Neut\|Number=Ptan\|POS=NOUN`, `Case=Ins\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Animacy=Nhum\|Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Nhum\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Neut\|NumForm=Word\|NumType=Sets\|Number=Plur\|POS=NUM`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `POS=PART`, `Aspect=Perf\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Degree=Pos\|POS=ADV`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Case=Gen\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `POS=SCONJ`, `Case=Dat\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|NumType=Sets\|Number=Sing\|POS=NOUN`, `Animacy=Hum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Loc\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Ins\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Nhum\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Neut\|NumType=Sets\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Aspect=Perf\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Nhum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Animacy=Hum\|Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Hyph=Yes\|POS=ADJ`, `POS=PUNCT\|PunctType=Dash`, `Animacy=Inan\|Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Perf\|Case=Ins\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Perf\|Case=Gen\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Nhum\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Ins\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Aspect=Imp\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Loc\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Aspect=Perf\|Case=Ins\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Inan\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Nom\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `POS=ADV\|PronType=Rel`, `Animacy=Hum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Inan\|Aspect=Perf\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Aspect=Imp\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Aspect=Perf\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Animacy=Nhum\|Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Ins\|Gender=Fem\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Hum\|Case=Dat\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Degree=Cmp\|POS=ADV`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Aspect=Perf\|Case=Loc\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Case=Nom\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Hum\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Animacy=Hum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Ins\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Nhum\|Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Nhum\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Animacy=Nhum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Aspect=Perf\|Gender=Neut\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Hum\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Aspect=Imp\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Nhum\|Case=Ins\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Nhum\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Animacy=Nhum\|Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Nhum\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Gen\|Gender=Neut\|Number=Ptan\|POS=NOUN`, `Aspect=Imp\|Case=Ins\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Inan\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Aspect=Perf\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|Number=Ptan\|POS=NOUN`, `Aspect=Imp\|Case=Nom\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|NumType=Card\|Number=Sing\|POS=DET\|PronType=Ind`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Aspect=Imp\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Hum\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Dat\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Aspect=Imp\|Case=Acc\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `POS=ADV\|PronType=Dem`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Ind`, `Animacy=Nhum\|Aspect=Perf\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Inan\|Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Aspect=Perf\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `Case=Acc\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Hum\|Case=Ins\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Loc\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Neut\|NumType=Sets\|Number=Plur\|POS=NOUN`, `Case=Loc\|Gender=Fem\|NumForm=Word\|Number=Plur\|POS=NUM`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Loc\|Gender=Neut\|NumType=Sets\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Inan\|Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Ptan\|POS=PRON\|PronType=Tot`, `Animacy=Nhum\|Aspect=Perf\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Aspect=Perf\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Nhum\|Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|NumType=Sets\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Aspect=Perf\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Inan\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Fem\|NumForm=Word\|Number=Plur\|POS=NUM`, `Degree=Pos\|POS=ADV\|PronType=Dem`, `Aspect=Imp\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Nhum\|Case=Acc\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Aspect=Perf\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Nom\|Gender=Neut\|Number=Ptan\|POS=NOUN`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Inan\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Rel`, `Animacy=Nhum\|Aspect=Imp\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Aspect=Imp\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Loc\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Dat\|Gender=Fem\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Rel`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Neut\|NumType=Sets\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Aspect=Perf\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Rel`, `Animacy=Nhum\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Nhum\|Aspect=Perf\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Rel`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Rel`, `Case=Dat\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Aspect=Imp\|Case=Dat\|Gender=Fem\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Gender=Neut\|NumForm=Word\|Number=Plur\|POS=NUM`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Case=Nom\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Aspect=Imp\|Case=Gen\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Aspect=Imp\|Case=Ins\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Loc\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `ConjType=Comp\|POS=SCONJ`, `Animacy=Inan\|Aspect=Imp\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Loc\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Aspect=Imp\|Case=Dat\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Animacy=Inan\|Aspect=Imp\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Nom\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|VerbType=Quasi`, `Animacy=Hum\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `POS=ADJ\|PrepCase=Pre`, `Animacy=Inan\|Aspect=Perf\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Animacy=Nhum\|Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Ins\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Aspect=Perf\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Nhum\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Acc\|Gender=Neut\|NumType=Sets\|Number=Plur\|POS=NOUN`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Case=Ins\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Animacy=Hum\|Aspect=Perf\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Neut\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Animacy=Hum\|Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Animacy=Nhum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Animacy=Hum\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Tot`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Aspect=Imp\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Animacy=Hum\|Aspect=Imp\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Aspect=Perf\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Hum\|Aspect=Imp,Perf\|Clitic=Yes\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|Variant=Long\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `POS=PUNCT\|PunctType=Excl`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Gender=Neut\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Aspect=Perf\|POS=VERB\|Tense=Past\|VerbForm=Conv\|Voice=Act`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Aspect=Imp\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Foreign=Yes\|POS=X`, `POS=PART\|Polarity=Neg`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Aspect=Imp\|Gender=Neut\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Aspect=Imp\|Clitic=Yes\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|Variant=Short\|VerbForm=Fin\|Voice=Act`, `Animacy=Hum\|Aspect=Imp,Perf\|Clitic=Yes\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Past\|Variant=Long\|VerbForm=Fin\|Voice=Act`, `Degree=Pos\|POS=ADV\|PronType=Int`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Neg`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Int`, `POS=PUNCT\|PunctType=Qest`, `Animacy=Inan\|Case=Nom\|Degree=Pos\|Gender=Masc\|NumForm=Roman\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Short`, `Animacy=Hum\|Aspect=Imp,Perf\|Clitic=Yes\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|Variant=Short\|VerbForm=Fin\|Voice=Act`, `Aspect=Imp\|Case=Loc\|Gender=Neut\|Number=Sing\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `POS=ADV\|PronType=Int`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs\|Variant=Short`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Tot`, `Animacy=Hum\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Act`, `Animacy=Hum\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Aspect=Imp\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Pre\|PronType=Prs\|Variant=Long`, `Animacy=Inan\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Loc\|Gender=Neut\|Number=Ptan\|POS=PROPN`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Int`, `POS=ADV\|PronType=Neg`, `Animacy=Hum\|Aspect=Imp\|Clitic=Yes\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|Variant=Long\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|NumForm=Word\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Neg`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Int`, `Animacy=Nhum\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Animacy=Hum\|Aspect=Perf\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Animacy=Hum\|Case=Acc\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Dat\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Aspect=Imp\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|VerbType=Mod\|Voice=Act`, `POS=PART\|PartType=Int`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `POS=ADV\|PronType=Ind`, `Animacy=Hum\|Case=Ins\|Gender=Masc\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Animacy=Hum\|Aspect=Perf\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=ADJ\|Polarity=Pos\|VerbForm=Part\|Voice=Pass`, `Animacy=Hum\|Aspect=Imp\|Clitic=Yes\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|Variant=Short\|VerbForm=Fin\|Voice=Act`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Acc\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Hum\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PrepCase=Npr\|PronType=Prs\|Variant=Long`, `Animacy=Hum\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|POS=VERB\|Person=0\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|NumForm=Digit\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Neut\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Aspect=Perf\|Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN\|Polarity=Pos\|VerbForm=Vnoun`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs\|Variant=Short`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Loc\|Gender=Fem\|NumType=Card\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Neg`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `POS=PART\|PartType=Mod`, `Aspect=Imp\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|POS=AUX\|VerbForm=Inf\|Voice=Act`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Neg`, _(truncated: full list in pipeline meta)_ | | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advcl:cmpr`, `advcl:relcl`, `advmod`, `advmod:arg`, `advmod:emph`, `advmod:neg`, `amod`, `amod:flat`, `appos`, `aux`, `aux:cnd`, `aux:imp`, `aux:pass`, `case`, `cc`, `cc:preconj`, `ccomp`, `ccomp:cleft`, `ccomp:obj`, `conj`, `cop`, `csubj`, `dep`, `det`, `det:numgov`, `det:nummod`, `det:poss`, `discourse:intj`, `expl:pv`, `fixed`, `flat`, `flat:foreign`, `iobj`, `list`, `mark`, `nmod`, `nmod:arg`, `nmod:flat`, `nmod:poss`, `nsubj`, `nsubj:pass`, `nummod`, `nummod:gov`, `obj`, `obl`, `obl:agent`, `obl:arg`, `obl:cmpr`, `orphan`, `parataxis:insert`, `parataxis:obj`, `punct`, `vocative`, `xcomp`, `xcomp:cleft`, `xcomp:pred` | | **`tagger`** | `ADJ`, `ADJA`, `ADJC`, `ADJP`, `ADV`, `AGLT`, `BEDZIE`, `BREV`, `BURK`, `COMP`, `CONJ`, `DEPR`, `FIN`, `GER`, `IMPS`, `IMPT`, `INF`, `INTERJ`, `INTERP`, `NUM`, `NUMCOL`, `PACT`, `PANT`, `PCON`, `PPAS`, `PPRON12`, `PPRON3`, `PRAET`, `PRED`, `PREP`, `QUB`, `SIEBIE`, `SUBST`, `WINIEN`, `XXX`, `_SP` | | **`ner`** | `date`, `geogName`, `orgName`, `persName`, `placeName`, `time` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.98 | | `TOKEN_P` | 99.63 | | `TOKEN_R` | 99.83 | | `TOKEN_F` | 99.73 | | `POS_ACC` | 97.06 | | `MORPH_ACC` | 87.97 | | `MORPH_MICRO_P` | 93.82 | | `MORPH_MICRO_R` | 93.59 | | `MORPH_MICRO_F` | 93.70 | | `SENTS_P` | 96.16 | | `SENTS_R` | 95.98 | | `SENTS_F` | 96.07 | | `DEP_UAS` | 87.75 | | `DEP_LAS` | 79.69 | | `LEMMA_ACC` | 93.09 | | `TAG_ACC` | 97.94 | | `ENTS_P` | 80.19 | | `ENTS_R` | 79.99 | | `ENTS_F` | 80.09 |
spacy/pt_core_news_lg
spacy
2023-10-10T06:40:05Z
15
4
spacy
[ "spacy", "token-classification", "pt", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - pt license: cc-by-sa-4.0 model-index: - name: pt_core_news_lg results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.9016596045 - name: NER Recall type: recall value: 0.9045519847 - name: NER F Score type: f_score value: 0.9031034788 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.8951305295 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9694357755 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.958640844 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9730077757 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.9021776702 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8624265468 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9512921022 --- ### Details: https://spacy.io/models/pt#pt_core_news_lg Portuguese pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner, attribute_ruler. | Feature | Description | | --- | --- | | **Name** | `pt_core_news_lg` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) | | **Sources** | [UD Portuguese Bosque v2.8](https://github.com/UniversalDependencies/UD_Portuguese-Bosque) (Rademaker, Alexandre; Freitas, Cláudia; de Souza, Elvis; Silveira, Aline; Cavalcanti, Tatiana; Evelyn, Wograine; Rocha, Luisa; Soares-Bastos, Isabela; Bick, Eckhard; Chalub, Fabricio; Paulino-Passos, Guilherme; Real, Livy; de Paiva, Valeria; Zeman, Daniel; Popel, Martin; Mareček, David; Silveira, Natalia; Martins, André)<br />[WikiNER](https://figshare.com/articles/Learning_multilingual_named_entity_recognition_from_Wikipedia/5462500) (Joel Nothman, Nicky Ringland, Will Radford, Tara Murphy, James R Curran)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (590 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=NOUN`, `Gender=Masc\|Number=Sing\|POS=ADJ`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=PROPN`, `Number=Sing\|POS=PROPN`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=NOUN`, `Definite=Def\|POS=ADP\|PronType=Art`, `Gender=Fem\|Number=Sing\|POS=NOUN`, `Gender=Fem\|Number=Sing\|POS=ADJ`, `POS=PUNCT`, `NumType=Card\|POS=NUM`, `POS=ADV`, `Gender=Fem\|Number=Plur\|POS=ADJ`, `Gender=Fem\|Number=Plur\|POS=NOUN`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=ADP\|PronType=Art`, `Gender=Fem\|Number=Sing\|POS=PROPN`, `Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part`, `POS=ADP`, `POS=PRON\|PronType=Rel`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `POS=SCONJ`, `POS=VERB\|VerbForm=Inf`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Plur\|POS=ADJ`, `POS=CCONJ`, `Definite=Def\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=ADP\|PronType=Art`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Rel`, `Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `POS=ADV\|Polarity=Neg`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Art`, `POS=X`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Dem`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Tot`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Number=Sing\|POS=CCONJ`, `Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Ind`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Number=Plur\|POS=NOUN`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `POS=AUX\|VerbForm=Inf`, `Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=ADP\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `POS=VERB\|VerbForm=Ger`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Gender=Masc\|Number=Plur\|POS=PROPN`, `Number=Plur\|POS=AUX\|Person=3\|VerbForm=Inf`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Dem`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Ind`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Art`, `POS=VERB\|VerbForm=Part`, `Gender=Masc\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=ADP\|PronType=Art`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Rel`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=ADP\|PronType=Art`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Gender=Fem\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Prs`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Gender=Masc\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `NumType=Ord\|POS=ADJ`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Ind`, `Number=Plur\|POS=ADJ`, `Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=SCONJ\|PronType=Dem`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Ind`, `Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part`, `Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part`, `Gender=Masc\|NumType=Mult\|Number=Sing\|POS=NUM`, `Number=Sing\|POS=PRON\|PronType=Ind`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Rel`, `Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Gender=Masc\|Number=Sing\|POS=PROPN\|PronType=Art`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Sing\|POS=VERB\|Person=3\|VerbForm=Inf`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Cnd\|Number=Sing\|POS=AUX\|Person=3\|VerbForm=Fin`, `POS=AUX\|VerbForm=Part`, `POS=SPACE`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Number=Sing\|POS=PRON\|PronType=Rel`, `Number=Sing\|POS=DET\|PronType=Art`, `Definite=Def\|Gender=Fem\|Number=Plur\|POS=ADP\|PronType=Art`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Gender=Masc\|NumType=Frac\|Number=Sing\|POS=NUM`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=ADP\|PronType=Dem`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Gender=Fem\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Number=Plur\|POS=VERB\|Person=3\|VerbForm=Inf`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=SCONJ\|PronType=Art`, `Definite=Def\|POS=SCONJ\|PronType=Art`, `Gender=Masc\|Number=Plur\|POS=ADP\|PronType=Art`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pqp\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Dem`, `Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Acc\|POS=PRON\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin`, `POS=AUX`, `Case=Acc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=ADP\|PronType=Art`, `Gender=Fem\|Number=Sing\|POS=ADP\|PronType=Art`, `POS=INTJ`, `Case=Acc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Number=Sing\|POS=PRON\|PronType=Int`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Rel`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Emp`, `Case=Acc\|Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|POS=PRON\|PronType=Ind`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Rel`, `Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Definite=Ind\|Gender=Masc\|Number=Sing\|POS=ADP\|PronType=Art`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Tense=Pqp\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Past\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|POS=VERB\|PronType=Prs\|VerbForm=Inf`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Fut\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Emp`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Gender=Masc\|Number=Plur\|POS=NOUN\|Voice=Pass`, `Gender=Fem\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Acc\|POS=VERB\|PronType=Prs\|VerbForm=Ger`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Acc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Imp\|VerbForm=Fin`, `Number=Sing\|POS=ADJ`, `Mood=Cnd\|Number=Sing\|POS=VERB\|Person=1\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Tot`, `Gender=Masc\|Number=Plur\|POS=ADP\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Number=Sing\|POS=AUX\|Person=3\|VerbForm=Inf`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Int`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Int`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int`, `Gender=Masc\|Number=Sing\|POS=NUM`, `Number=Sing\|POS=NOUN`, `Case=Acc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Fut\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=ADP\|PronType=Art`, `Gender=Fem\|Number=Plur\|POS=ADP\|PronType=Dem`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=PART`, `Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Plur\|POS=DET\|PronType=Ind`, `Case=Acc\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Gender=Masc\|Number=Sing\|POS=ADV`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Rel`, `Case=Dat\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Neg`, `Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|VerbForm=Ger`, `NumType=Card\|POS=DET`, `Number=Plur\|POS=VERB\|Person=1\|VerbForm=Inf`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Int`, `Mood=Cnd\|Number=Plur\|POS=AUX\|Person=3\|VerbForm=Fin`, `Gender=Masc\|POS=ADJ`, `POS=NOUN`, `POS=AUX\|VerbForm=Ger`, `Case=Dat\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=SCONJ\|PronType=Art`, `Case=Acc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Fut\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Art`, `Gender=Fem\|Number=Sing\|POS=DET`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Art`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Imp\|VerbForm=Fin`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Emp`, `POS=PRON\|PronType=Prs`, `Gender=Masc\|Number=Plur\|POS=DET`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Case=Dat\|Gender=Masc\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=AUX\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Tot`, `Definite=Def\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Masc\|POS=PRON\|PronType=Prs`, `POS=VERB\|VerbForm=Fin`, `Gender=Masc\|NumType=Card\|Number=Sing\|POS=NUM`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=DET\|PronType=Neg`, `POS=VERB\|VerbForm=Inf\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=AUX\|VerbForm=Part`, `Case=Acc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Inf`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=1\|Tense=Imp\|VerbForm=Fin`, `Number=Sing\|POS=PROPN\|PronType=Art`, `Case=Dat\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|PronType=Prs\|Tense=Imp\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=1\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pqp\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Gender=Fem\|Number=Sing\|POS=ADJ\|PronType=Dem`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Imp\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Number=Plur\|POS=AUX\|Person=1\|Tense=Past`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Past\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Neg`, `POS=PRON\|PronType=Dem`, `Gender=Masc\|Number=Sing\|POS=DET`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=ADV\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `POS=PRON\|PronType=Ind`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Fut\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Tot`, `Case=Dat\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|POS=VERB\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=X`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=DET\|PronType=Rel`, `Gender=Masc\|Number=Sing\|POS=SCONJ`, `Gender=Masc\|Number=Sing\|POS=PRON`, `Gender=Fem\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Definite=Def\|Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Case=Acc\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Imp\|VerbForm=Fin`, `POS=ADP\|PronType=Dem`, `Definite=Def\|Gender=Fem\|POS=ADP\|PronType=Art`, `POS=ADP\|PronType=Art`, `Gender=Masc\|Number=Sing\|POS=ADP`, `Gender=Masc\|Number=Sing\|POS=ADP\|Person=3\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pqp\|VerbForm=Fin`, `Case=Dat\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Imp\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Imp\|VerbForm=Fin`, `Case=Dat\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `POS=DET`, `Gender=Fem\|Number=Plur\|POS=DET\|PronType=Emp`, `Definite=Def\|Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Art`, `Case=Acc\|Gender=Masc\|Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Number=Plur\|POS=AUX\|Person=1\|VerbForm=Inf`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Degree=Cmp\|POS=ADJ`, `Gender=Fem\|Number=Plur\|POS=ADP\|PronType=Ind`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Dem`, `Case=Acc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Imp\|VerbForm=Fin`, `Number=Sing\|POS=VERB\|Person=3\|VerbForm=Inf\|Voice=Pass`, `Mood=Sub\|Number=Plur\|POS=AUX\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Number=Plur\|POS=VERB\|Person=2\|PronType=Prs\|VerbForm=Inf`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem,Masc\|Number=Sing\|POS=PROPN`, `POS=PRON\|PronType=Int`, `Gender=Fem\|Number=Plur\|POS=NUM`, `POS=PRON\|PronType=Neg`, `Gender=Fem\|Number=Sing\|POS=SCONJ\|PronType=Dem`, `POS=SYM`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pqp\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=X`, `Case=Dat\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Gender=Masc\|NumType=Sets\|Number=Sing\|POS=NUM`, `Foreign=Yes\|POS=NOUN`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Case=Acc\|POS=AUX\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Number=Sing\|POS=DET\|PronType=Ind`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Number=Plur\|POS=PRON\|PronType=Int`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=SCONJ\|PronType=Art`, `Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Prs`, `Number=Sing\|POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Imp\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=ADP\|PronType=Ind`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Definite=Ind\|Gender=Fem\|Number=Sing\|POS=SCONJ\|PronType=Art`, `Number=Sing\|POS=VERB`, `Number=Sing\|POS=DET`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=3\|VerbForm=Fin\|Voice=Pass`, `NumType=Mult\|POS=NUM`, `Gender=Fem\|Number=Sing\|POS=PRON\|PronType=Neg`, `Mood=Ind\|POS=VERB\|Tense=Imp\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Case=Acc\|Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Fut\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=SCONJ\|PronType=Rel`, `Case=Acc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `Gender=Masc\|Number=Sing\|POS=ADV\|Polarity=Neg`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Imp\|VerbForm=Fin`, `Case=Acc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=VERB\|Person=1\|PronType=Prs\|VerbForm=Inf`, `Number=Sing\|POS=VERB\|Person=1\|VerbForm=Inf`, `Definite=Def\|Gender=Masc\|POS=ADP\|PronType=Art`, `Gender=Masc\|POS=NOUN`, `Gender=Masc\|NumType=Ord\|Number=Sing\|POS=NOUN`, `Definite=Def\|Gender=Fem\|Number=Plur\|POS=SCONJ\|PronType=Art`, `POS=ADJ`, `Gender=Fem\|Number=Sing\|POS=ADV\|PronType=Ind`, `Mood=Sub\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Prs`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Acc\|Number=Plur\|POS=VERB\|Person=1\|PronType=Prs\|VerbForm=Inf`, `Number=Sing\|POS=PRON\|PronType=Tot`, `Number=Sing\|POS=DET\|PronType=Rel`, `Gender=Fem\|Number=Plur\|POS=VERB`, `Case=Dat\|Gender=Fem\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Masc\|Number=Plur,Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|PronType=Prs\|VerbForm=Inf`, `Number=Sing\|POS=DET\|PronType=Tot`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `NumType=Range\|POS=NUM`, `Case=Dat\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Dat\|Gender=Masc\|Mood=Cnd\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Mood=Cnd\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Fin`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Mood=Sub\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Fut\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=VERB\|Person=1\|PronType=Prs\|VerbForm=Inf`, `Case=Dat\|Gender=Masc\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Int`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Imp\|VerbForm=Fin`, `Number=Sing\|POS=VERB\|Person=1\|VerbForm=Inf\|Voice=Pass`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Imp\|VerbForm=Fin`, `Gender=Masc\|Number=Plur\|POS=SCONJ\|PronType=Dem`, `NumType=Frac\|POS=NUM`, `Gender=Masc\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=ADP\|PronType=Ind`, `Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|VerbForm=Fin`, `Gender=Fem\|Number=Sing\|POS=ADV\|PronType=Rel`, `Mood=Cnd\|POS=VERB\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Mood=Cnd\|Number=Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Dat\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Imp\|VerbForm=Fin`, `Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=ADP\|PronType=Ind`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf\|Voice=Pass`, `POS=VERB\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Mood=Cnd\|Number=Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Number=Sing\|POS=X`, `POS=PROPN`, `Mood=Cnd\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin`, `Case=Acc\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Gender=Masc\|Number=Sing\|POS=ADV\|PronType=Int`, `Case=Dat\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=1,3\|PronType=Prs\|Tense=Past\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|VerbForm=Inf`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Imp\|VerbForm=Fin\|Voice=Pass`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc,Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Int`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Tense=Pqp\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|POS=AUX\|PronType=Prs\|VerbForm=Ger`, `Case=Acc\|Gender=Fem\|POS=AUX\|PronType=Prs\|VerbForm=Ger`, `Case=Acc\|Gender=Fem\|Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Dat\|Number=Plur\|POS=VERB\|Person=1\|PronType=Prs\|VerbForm=Inf`, `Case=Acc\|Gender=Masc\|Mood=Sub\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs\|VerbForm=Ger`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Tense=Fut\|VerbForm=Fin`, `Case=Acc\|Mood=Ind\|Number=Plur,Sing\|POS=VERB\|Person=1,3\|PronType=Prs\|Tense=Imp\|VerbForm=Fin`, `Gender=Fem\|Number=Plur\|POS=PRON\|PronType=Prs`, `Gender=Fem\|Number=Plur\|POS=X`, `Definite=Def\|Gender=Masc\|Number=Plur\|POS=PRON\|PronType=Rel`, `Definite=Ind\|Gender=Fem\|POS=DET\|PronType=Art`, `Case=Acc\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Pqp\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin`, `Mood=Sub\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Number=Sing\|POS=NUM`, `Number=Plur\|POS=PROPN`, `Case=Dat\|POS=PRON\|PronType=Prs`, `Gender=Masc\|Number=Sing\|POS=VERB`, `Case=Acc\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|PronType=Prs\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, _(truncated: full list in pipeline meta)_ | | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `ccomp`, `compound`, `conj`, `cop`, `csubj`, `dep`, `det`, `discourse`, `expl`, `fixed`, `flat`, `flat:foreign`, `flat:name`, `iobj`, `mark`, `nmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `obl:agent`, `parataxis`, `punct`, `xcomp` | | **`ner`** | `LOC`, `MISC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 100.00 | | `TOKEN_P` | 99.88 | | `TOKEN_R` | 99.95 | | `TOKEN_F` | 99.92 | | `POS_ACC` | 96.94 | | `MORPH_ACC` | 95.86 | | `MORPH_MICRO_P` | 98.21 | | `MORPH_MICRO_R` | 97.69 | | `MORPH_MICRO_F` | 97.95 | | `SENTS_P` | 93.99 | | `SENTS_R` | 96.30 | | `SENTS_F` | 95.13 | | `DEP_UAS` | 90.22 | | `DEP_LAS` | 86.24 | | `LEMMA_ACC` | 97.30 | | `TAG_ACC` | 89.51 | | `ENTS_P` | 90.17 | | `ENTS_R` | 90.46 | | `ENTS_F` | 90.31 |
spacy/ro_core_news_lg
spacy
2023-10-10T06:39:13Z
17
2
spacy
[ "spacy", "token-classification", "ro", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - ro license: cc-by-sa-4.0 model-index: - name: ro_core_news_lg results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7502799552 - name: NER Recall type: recall value: 0.7721859393 - name: NER F Score type: f_score value: 0.7610753502 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9657255109 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9395242502 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9499516228 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9575746914 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8875784191 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8359473024 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9699799867 --- ### Details: https://spacy.io/models/ro#ro_core_news_lg Romanian pipeline optimized for CPU. Components: tok2vec, tagger, parser, lemmatizer (trainable_lemmatizer), senter, ner, attribute_ruler. | Feature | Description | | --- | --- | | **Name** | `ro_core_news_lg` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) | | **Sources** | [UD Romanian RRT v2.8](https://github.com/UniversalDependencies/UD_Romanian-RRT) (Barbu Mititelu, Verginica; Irimia, Elena; Perez, Cenel-Augusto; Ion, Radu; Simionescu, Radu; Popel, Martin)<br />[RONEC - the Romanian Named Entity Corpus (ca9ce460)](https://github.com/dumitrescustefan/ronec) (Dumitrescu, Stefan Daniel; Avram, Andrei-Marius; Morogan, Luciana; Toma; Stefan)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (540 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `ARROW`, `Af`, `Afcfp-n`, `Afcfson`, `Afcfsrn`, `Afcmpoy`, `Afcms-n`, `Afp`, `Afp-p-n`, `Afp-poy`, `Afp-srn`, `Afpf--n`, `Afpfp-n`, `Afpfp-ny`, `Afpfpoy`, `Afpfpry`, `Afpfson`, `Afpfsoy`, `Afpfsrn`, `Afpfsry`, `Afpm--n`, `Afpmp-n`, `Afpmpoy`, `Afpmpry`, `Afpms-n`, `Afpmsoy`, `Afpmsry`, `Afsfp-n`, `Afsfsrn`, `BULLET`, `COLON`, `COMMA`, `Ccssp`, `Ccsspy`, `Crssp`, `Csssp`, `Cssspy`, `DASH`, `DBLQ`, `Dd3-po---e`, `Dd3-po---o`, `Dd3fpo`, `Dd3fpr`, `Dd3fpr---e`, `Dd3fpr---o`, `Dd3fpr--y`, `Dd3fso`, `Dd3fso---e`, `Dd3fsr`, `Dd3fsr---e`, `Dd3fsr---o`, `Dd3fsr--yo`, `Dd3mpo`, `Dd3mpr`, `Dd3mpr---e`, `Dd3mpr---o`, `Dd3mso---e`, `Dd3msr`, `Dd3msr---e`, `Dd3msr---o`, `Dh1ms`, `Dh3fp`, `Dh3fso`, `Dh3fsr`, `Dh3mp`, `Dh3ms`, `Di3`, `Di3-----y`, `Di3--r---e`, `Di3-po`, `Di3-po---e`, `Di3-sr`, `Di3-sr---e`, `Di3-sr--y`, `Di3fp`, `Di3fpr`, `Di3fpr---e`, `Di3fso`, `Di3fso---e`, `Di3fsr`, `Di3fsr---e`, `Di3mp`, `Di3mpr`, `Di3mpr---e`, `Di3ms`, `Di3ms----e`, `Di3mso---e`, `Di3msr`, `Di3msr---e`, `Ds1fp-p`, `Ds1fp-s`, `Ds1fsop`, `Ds1fsos`, `Ds1fsrp`, `Ds1fsrs`, `Ds1fsrs-y`, `Ds1mp-p`, `Ds1mp-s`, `Ds1ms-p`, `Ds1ms-s`, `Ds1msrs-y`, `Ds2---s`, `Ds2fp-p`, `Ds2fp-s`, `Ds2fsrp`, `Ds2fsrs`, `Ds2mp-p`, `Ds2mp-s`, `Ds2ms-p`, `Ds2ms-s`, `Ds3---p`, `Ds3---s`, `Ds3---sy`, `Ds3fp-s`, `Ds3fsos`, `Ds3fsrs`, `Ds3mp-s`, `Ds3ms-s`, `Dw3--r---e`, `Dw3-po---e`, `Dw3fpr`, `Dw3fso---e`, `Dw3fsr`, `Dw3mpr`, `Dw3mso---e`, `Dw3msr`, `Dz3fsr---e`, `Dz3mso---e`, `Dz3msr---e`, `EQUAL`, `EXCL`, `EXCLHELLIP`, `GE`, `GT`, `HELLIP`, `I`, `LCURL`, `LPAR`, `LSQR`, `LT`, `M`, `Mc-p-d`, `Mc-p-l`, `Mc-s-b`, `Mc-s-d`, `Mc-s-l`, `Mcfp-l`, `Mcfp-ln`, `Mcfprln`, `Mcfprly`, `Mcfsoln`, `Mcfsrl`, `Mcfsrln`, `Mcfsrly`, `Mcmp-l`, `Mcms-ln`, `Mcmsrl`, `Mcmsrln`, `Mcmsrly`, `Mffprln`, `Mffsrln`, `Mlfpo`, `Mlfpr`, `Mlmpr`, `Mo---l`, `Mo---ln`, `Mo-s-r`, `Mofp-ln`, `Mofpoly`, `Mofprly`, `Mofs-l`, `Mofsoln`, `Mofsoly`, `Mofsrln`, `Mofsrly`, `Mompoly`, `Momprly`, `Moms-l`, `Moms-ln`, `Momsoly`, `Momsrly`, `Nc`, `Nc---n`, `Ncf--n`, `Ncfp-n`, `Ncfpoy`, `Ncfpry`, `Ncfs-n`, `Ncfson`, `Ncfsoy`, `Ncfsrn`, `Ncfsry`, `Ncfsryy`, `Ncfsvy`, `Ncm--n`, `Ncmp-n`, `Ncmpoy`, `Ncmpry`, `Ncms-n`, `Ncms-ny`, `Ncms-y`, `Ncmsoy`, `Ncmsrn`, `Ncmsry`, `Ncmsryy`, `Ncmsvn`, `Ncmsvy`, `Np`, `Npfson`, `Npfsoy`, `Npfsrn`, `Npfsry`, `Npmpoy`, `Npmpry`, `Npms-n`, `Npmsoy`, `Npmsry`, `PERCENT`, `PERIOD`, `PLUS`, `PLUSMINUS`, `Pd3-po`, `Pd3fpr`, `Pd3fso`, `Pd3fsr`, `Pd3mpo`, `Pd3mpr`, `Pd3mpr--y`, `Pd3mso`, `Pd3msr`, `Pi3--r`, `Pi3-po`, `Pi3-so`, `Pi3-sr`, `Pi3fpr`, `Pi3fso`, `Pi3fsr`, `Pi3mpr`, `Pi3mso`, `Pi3msr`, `Pi3msr--y`, `Pp1-pa--------w`, `Pp1-pa--y-----w`, `Pp1-pd--------s`, `Pp1-pd--------w`, `Pp1-pd--y-----w`, `Pp1-pr--------s`, `Pp1-sa--------s`, `Pp1-sa--------w`, `Pp1-sa--y-----w`, `Pp1-sd--------s`, `Pp1-sd--------w`, `Pp1-sd--y-----w`, `Pp1-sn--------s`, `Pp2-----------s`, `Pp2-pa--------w`, `Pp2-pa--y-----w`, `Pp2-pd--------w`, `Pp2-pd--y-----w`, `Pp2-pr--------s`, `Pp2-sa--------s`, `Pp2-sa--------w`, `Pp2-sa--y-----w`, `Pp2-sd--------s`, `Pp2-sd--------w`, `Pp2-sd--y-----w`, `Pp2-sn--------s`, `Pp2-so--------s`, `Pp2-sr--------s`, `Pp3-p---------s`, `Pp3-pd--------w`, `Pp3-pd--y-----w`, `Pp3-po--------s`, `Pp3-sd--------w`, `Pp3-sd--y-----w`, `Pp3-so--------s`, `Pp3fpa--------w`, `Pp3fpa--y-----w`, `Pp3fpr--------s`, `Pp3fs---------s`, `Pp3fsa--------w`, `Pp3fsa--y-----w`, `Pp3fso--------s`, `Pp3fsr--------s`, `Pp3fsr--y-----s`, `Pp3mpa--------w`, `Pp3mpa--y-----w`, `Pp3mpr--------s`, `Pp3ms---------s`, `Pp3msa--------w`, `Pp3msa--y-----w`, `Pp3mso--------s`, `Pp3msr--------s`, `Pp3msr--y-----s`, `Ps1fp-s`, `Ps1fsrp`, `Ps1fsrs`, `Ps1mp-p`, `Ps1ms-p`, `Ps2fp-s`, `Ps2fsrp`, `Ps2fsrs`, `Ps3---p`, `Ps3---s`, `Ps3fp-s`, `Ps3fsrs`, `Ps3mp-s`, `Ps3ms-s`, `Pw3--r`, `Pw3-po`, `Pw3-so`, `Pw3fpr`, `Pw3fso`, `Pw3mpr`, `Pw3mso`, `Px3--a--------s`, `Px3--a--------w`, `Px3--a--y-----w`, `Px3--d--------w`, `Px3--d--y-----w`, `Pz3-sr`, `Pz3fsr`, `QUEST`, `QUOT`, `Qf`, `Qn`, `Qs`, `Qs-y`, `Qz`, `Qz-y`, `RCURL`, `RPAR`, `RSQR`, `Rc`, `Rgp`, `Rgpy`, `Rgs`, `Rp`, `Rw`, `Rw-y`, `Rz`, `SCOLON`, `SLASH`, `STAR`, `Sp`, `Spsa`, `Spsay`, `Spsd`, `Spsg`, `Td-po`, `Tdfpr`, `Tdfso`, `Tdfsr`, `Tdmpr`, `Tdmso`, `Tdmsr`, `Tf-so`, `Tffpoy`, `Tffpry`, `Tffs-y`, `Tfmpoy`, `Tfms-y`, `Tfmsoy`, `Tfmsry`, `Ti-po`, `Tifp-y`, `Tifso`, `Tifsr`, `Timso`, `Timsr`, `Tsfp`, `Tsfs`, `Tsmp`, `Tsms`, `UNDERSC`, `Va--1`, `Va--1-----y`, `Va--1p`, `Va--1s`, `Va--1s----y`, `Va--2p`, `Va--2p----y`, `Va--2s`, `Va--2s----y`, `Va--3`, `Va--3-----y`, `Va--3p`, `Va--3p----y`, `Va--3s`, `Va--3s----y`, `Vag`, `Vag-------y`, `Vaii1`, `Vaii2s`, `Vaii3p`, `Vaii3s`, `Vail3p`, `Vail3s`, `Vaip1p`, `Vaip1s`, `Vaip2p`, `Vaip2s`, `Vaip3p`, `Vaip3p----y`, `Vaip3s`, `Vaip3s----y`, `Vais3p`, `Vais3s`, `Vam-2s`, `Vanp`, `Vap--sm`, `Vasp1p`, `Vasp1s`, `Vasp2p`, `Vasp2s`, `Vasp3`, `Vmg`, `Vmg-------y`, `Vmii1`, `Vmii1-----y`, `Vmii2p`, `Vmii2s`, `Vmii3p`, `Vmii3p----y`, `Vmii3s`, `Vmii3s----y`, `Vmil1`, `Vmil1p`, `Vmil2s`, `Vmil3p`, `Vmil3p----y`, `Vmil3s`, `Vmil3s----y`, `Vmip1p`, `Vmip1p----y`, `Vmip1s`, `Vmip1s----y`, `Vmip2p`, `Vmip2s`, `Vmip2s----y`, `Vmip3`, `Vmip3-----y`, `Vmip3p`, `Vmip3s`, `Vmip3s----y`, `Vmis1p`, `Vmis1s`, `Vmis3p`, `Vmis3p----y`, `Vmis3s`, `Vmis3s----y`, `Vmm-2p`, `Vmm-2s`, `Vmnp`, `Vmnp------y`, `Vmp--pf`, `Vmp--pm`, `Vmp--sf`, `Vmp--sm`, `Vmp--sm---y`, `Vmsp1p`, `Vmsp2p`, `Vmsp2s`, `Vmsp3`, `Vmsp3-----y`, `X`, `Y`, `Ya`, `Yn`, `Ynfsoy`, `Ynfsry`, `Ynmsoy`, `Ynmsry`, `Yp`, `Yp,Yn`, `Yp-sr`, `Yr`, `_SP` | | **`parser`** | `ROOT`, `acl`, `advcl`, `advcl:tcl`, `advmod`, `advmod:tmod`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `cc:preconj`, `ccomp`, `ccomp:pmod`, `compound`, `conj`, `cop`, `csubj`, `csubj:pass`, `dep`, `det`, `expl`, `expl:impers`, `expl:pass`, `expl:poss`, `expl:pv`, `fixed`, `flat`, `goeswith`, `iobj`, `mark`, `nmod`, `nmod:tmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `obl:agent`, `obl:pmod`, `orphan`, `parataxis`, `punct`, `vocative`, `xcomp` | | **`ner`** | `DATETIME`, `EVENT`, `FACILITY`, `GPE`, `LANGUAGE`, `LOC`, `MONEY`, `NAT_REL_POL`, `NUMERIC_VALUE`, `ORDINAL`, `ORGANIZATION`, `PERIOD`, `PERSON`, `PRODUCT`, `QUANTITY`, `WORK_OF_ART` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.80 | | `TOKEN_P` | 99.67 | | `TOKEN_R` | 99.57 | | `TOKEN_F` | 99.59 | | `TAG_ACC` | 96.57 | | `SENTS_P` | 97.32 | | `SENTS_R` | 96.68 | | `SENTS_F` | 97.00 | | `DEP_UAS` | 88.76 | | `DEP_LAS` | 83.59 | | `LEMMA_ACC` | 95.76 | | `POS_ACC` | 93.95 | | `MORPH_ACC` | 95.00 | | `MORPH_MICRO_P` | 99.05 | | `MORPH_MICRO_R` | 95.76 | | `MORPH_MICRO_F` | 97.04 | | `ENTS_P` | 75.03 | | `ENTS_R` | 77.22 | | `ENTS_F` | 76.11 |
spacy/ro_core_news_md
spacy
2023-10-10T06:38:24Z
4
0
spacy
[ "spacy", "token-classification", "ro", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - ro license: cc-by-sa-4.0 model-index: - name: ro_core_news_md results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7486792453 - name: NER Recall type: recall value: 0.7621974645 - name: NER F Score type: f_score value: 0.7553778793 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9628522004 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9367770732 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9477819802 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9532354062 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8855708908 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8341279799 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9607451763 --- ### Details: https://spacy.io/models/ro#ro_core_news_md Romanian pipeline optimized for CPU. Components: tok2vec, tagger, parser, lemmatizer (trainable_lemmatizer), senter, ner, attribute_ruler. | Feature | Description | | --- | --- | | **Name** | `ro_core_news_md` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 500000 keys, 20000 unique vectors (300 dimensions) | | **Sources** | [UD Romanian RRT v2.8](https://github.com/UniversalDependencies/UD_Romanian-RRT) (Barbu Mititelu, Verginica; Irimia, Elena; Perez, Cenel-Augusto; Ion, Radu; Simionescu, Radu; Popel, Martin)<br />[RONEC - the Romanian Named Entity Corpus (ca9ce460)](https://github.com/dumitrescustefan/ronec) (Dumitrescu, Stefan Daniel; Avram, Andrei-Marius; Morogan, Luciana; Toma; Stefan)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (540 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `ARROW`, `Af`, `Afcfp-n`, `Afcfson`, `Afcfsrn`, `Afcmpoy`, `Afcms-n`, `Afp`, `Afp-p-n`, `Afp-poy`, `Afp-srn`, `Afpf--n`, `Afpfp-n`, `Afpfp-ny`, `Afpfpoy`, `Afpfpry`, `Afpfson`, `Afpfsoy`, `Afpfsrn`, `Afpfsry`, `Afpm--n`, `Afpmp-n`, `Afpmpoy`, `Afpmpry`, `Afpms-n`, `Afpmsoy`, `Afpmsry`, `Afsfp-n`, `Afsfsrn`, `BULLET`, `COLON`, `COMMA`, `Ccssp`, `Ccsspy`, `Crssp`, `Csssp`, `Cssspy`, `DASH`, `DBLQ`, `Dd3-po---e`, `Dd3-po---o`, `Dd3fpo`, `Dd3fpr`, `Dd3fpr---e`, `Dd3fpr---o`, `Dd3fpr--y`, `Dd3fso`, `Dd3fso---e`, `Dd3fsr`, `Dd3fsr---e`, `Dd3fsr---o`, `Dd3fsr--yo`, `Dd3mpo`, `Dd3mpr`, `Dd3mpr---e`, `Dd3mpr---o`, `Dd3mso---e`, `Dd3msr`, `Dd3msr---e`, `Dd3msr---o`, `Dh1ms`, `Dh3fp`, `Dh3fso`, `Dh3fsr`, `Dh3mp`, `Dh3ms`, `Di3`, `Di3-----y`, `Di3--r---e`, `Di3-po`, `Di3-po---e`, `Di3-sr`, `Di3-sr---e`, `Di3-sr--y`, `Di3fp`, `Di3fpr`, `Di3fpr---e`, `Di3fso`, `Di3fso---e`, `Di3fsr`, `Di3fsr---e`, `Di3mp`, `Di3mpr`, `Di3mpr---e`, `Di3ms`, `Di3ms----e`, `Di3mso---e`, `Di3msr`, `Di3msr---e`, `Ds1fp-p`, `Ds1fp-s`, `Ds1fsop`, `Ds1fsos`, `Ds1fsrp`, `Ds1fsrs`, `Ds1fsrs-y`, `Ds1mp-p`, `Ds1mp-s`, `Ds1ms-p`, `Ds1ms-s`, `Ds1msrs-y`, `Ds2---s`, `Ds2fp-p`, `Ds2fp-s`, `Ds2fsrp`, `Ds2fsrs`, `Ds2mp-p`, `Ds2mp-s`, `Ds2ms-p`, `Ds2ms-s`, `Ds3---p`, `Ds3---s`, `Ds3---sy`, `Ds3fp-s`, `Ds3fsos`, `Ds3fsrs`, `Ds3mp-s`, `Ds3ms-s`, `Dw3--r---e`, `Dw3-po---e`, `Dw3fpr`, `Dw3fso---e`, `Dw3fsr`, `Dw3mpr`, `Dw3mso---e`, `Dw3msr`, `Dz3fsr---e`, `Dz3mso---e`, `Dz3msr---e`, `EQUAL`, `EXCL`, `EXCLHELLIP`, `GE`, `GT`, `HELLIP`, `I`, `LCURL`, `LPAR`, `LSQR`, `LT`, `M`, `Mc-p-d`, `Mc-p-l`, `Mc-s-b`, `Mc-s-d`, `Mc-s-l`, `Mcfp-l`, `Mcfp-ln`, `Mcfprln`, `Mcfprly`, `Mcfsoln`, `Mcfsrl`, `Mcfsrln`, `Mcfsrly`, `Mcmp-l`, `Mcms-ln`, `Mcmsrl`, `Mcmsrln`, `Mcmsrly`, `Mffprln`, `Mffsrln`, `Mlfpo`, `Mlfpr`, `Mlmpr`, `Mo---l`, `Mo---ln`, `Mo-s-r`, `Mofp-ln`, `Mofpoly`, `Mofprly`, `Mofs-l`, `Mofsoln`, `Mofsoly`, `Mofsrln`, `Mofsrly`, `Mompoly`, `Momprly`, `Moms-l`, `Moms-ln`, `Momsoly`, `Momsrly`, `Nc`, `Nc---n`, `Ncf--n`, `Ncfp-n`, `Ncfpoy`, `Ncfpry`, `Ncfs-n`, `Ncfson`, `Ncfsoy`, `Ncfsrn`, `Ncfsry`, `Ncfsryy`, `Ncfsvy`, `Ncm--n`, `Ncmp-n`, `Ncmpoy`, `Ncmpry`, `Ncms-n`, `Ncms-ny`, `Ncms-y`, `Ncmsoy`, `Ncmsrn`, `Ncmsry`, `Ncmsryy`, `Ncmsvn`, `Ncmsvy`, `Np`, `Npfson`, `Npfsoy`, `Npfsrn`, `Npfsry`, `Npmpoy`, `Npmpry`, `Npms-n`, `Npmsoy`, `Npmsry`, `PERCENT`, `PERIOD`, `PLUS`, `PLUSMINUS`, `Pd3-po`, `Pd3fpr`, `Pd3fso`, `Pd3fsr`, `Pd3mpo`, `Pd3mpr`, `Pd3mpr--y`, `Pd3mso`, `Pd3msr`, `Pi3--r`, `Pi3-po`, `Pi3-so`, `Pi3-sr`, `Pi3fpr`, `Pi3fso`, `Pi3fsr`, `Pi3mpr`, `Pi3mso`, `Pi3msr`, `Pi3msr--y`, `Pp1-pa--------w`, `Pp1-pa--y-----w`, `Pp1-pd--------s`, `Pp1-pd--------w`, `Pp1-pd--y-----w`, `Pp1-pr--------s`, `Pp1-sa--------s`, `Pp1-sa--------w`, `Pp1-sa--y-----w`, `Pp1-sd--------s`, `Pp1-sd--------w`, `Pp1-sd--y-----w`, `Pp1-sn--------s`, `Pp2-----------s`, `Pp2-pa--------w`, `Pp2-pa--y-----w`, `Pp2-pd--------w`, `Pp2-pd--y-----w`, `Pp2-pr--------s`, `Pp2-sa--------s`, `Pp2-sa--------w`, `Pp2-sa--y-----w`, `Pp2-sd--------s`, `Pp2-sd--------w`, `Pp2-sd--y-----w`, `Pp2-sn--------s`, `Pp2-so--------s`, `Pp2-sr--------s`, `Pp3-p---------s`, `Pp3-pd--------w`, `Pp3-pd--y-----w`, `Pp3-po--------s`, `Pp3-sd--------w`, `Pp3-sd--y-----w`, `Pp3-so--------s`, `Pp3fpa--------w`, `Pp3fpa--y-----w`, `Pp3fpr--------s`, `Pp3fs---------s`, `Pp3fsa--------w`, `Pp3fsa--y-----w`, `Pp3fso--------s`, `Pp3fsr--------s`, `Pp3fsr--y-----s`, `Pp3mpa--------w`, `Pp3mpa--y-----w`, `Pp3mpr--------s`, `Pp3ms---------s`, `Pp3msa--------w`, `Pp3msa--y-----w`, `Pp3mso--------s`, `Pp3msr--------s`, `Pp3msr--y-----s`, `Ps1fp-s`, `Ps1fsrp`, `Ps1fsrs`, `Ps1mp-p`, `Ps1ms-p`, `Ps2fp-s`, `Ps2fsrp`, `Ps2fsrs`, `Ps3---p`, `Ps3---s`, `Ps3fp-s`, `Ps3fsrs`, `Ps3mp-s`, `Ps3ms-s`, `Pw3--r`, `Pw3-po`, `Pw3-so`, `Pw3fpr`, `Pw3fso`, `Pw3mpr`, `Pw3mso`, `Px3--a--------s`, `Px3--a--------w`, `Px3--a--y-----w`, `Px3--d--------w`, `Px3--d--y-----w`, `Pz3-sr`, `Pz3fsr`, `QUEST`, `QUOT`, `Qf`, `Qn`, `Qs`, `Qs-y`, `Qz`, `Qz-y`, `RCURL`, `RPAR`, `RSQR`, `Rc`, `Rgp`, `Rgpy`, `Rgs`, `Rp`, `Rw`, `Rw-y`, `Rz`, `SCOLON`, `SLASH`, `STAR`, `Sp`, `Spsa`, `Spsay`, `Spsd`, `Spsg`, `Td-po`, `Tdfpr`, `Tdfso`, `Tdfsr`, `Tdmpr`, `Tdmso`, `Tdmsr`, `Tf-so`, `Tffpoy`, `Tffpry`, `Tffs-y`, `Tfmpoy`, `Tfms-y`, `Tfmsoy`, `Tfmsry`, `Ti-po`, `Tifp-y`, `Tifso`, `Tifsr`, `Timso`, `Timsr`, `Tsfp`, `Tsfs`, `Tsmp`, `Tsms`, `UNDERSC`, `Va--1`, `Va--1-----y`, `Va--1p`, `Va--1s`, `Va--1s----y`, `Va--2p`, `Va--2p----y`, `Va--2s`, `Va--2s----y`, `Va--3`, `Va--3-----y`, `Va--3p`, `Va--3p----y`, `Va--3s`, `Va--3s----y`, `Vag`, `Vag-------y`, `Vaii1`, `Vaii2s`, `Vaii3p`, `Vaii3s`, `Vail3p`, `Vail3s`, `Vaip1p`, `Vaip1s`, `Vaip2p`, `Vaip2s`, `Vaip3p`, `Vaip3p----y`, `Vaip3s`, `Vaip3s----y`, `Vais3p`, `Vais3s`, `Vam-2s`, `Vanp`, `Vap--sm`, `Vasp1p`, `Vasp1s`, `Vasp2p`, `Vasp2s`, `Vasp3`, `Vmg`, `Vmg-------y`, `Vmii1`, `Vmii1-----y`, `Vmii2p`, `Vmii2s`, `Vmii3p`, `Vmii3p----y`, `Vmii3s`, `Vmii3s----y`, `Vmil1`, `Vmil1p`, `Vmil2s`, `Vmil3p`, `Vmil3p----y`, `Vmil3s`, `Vmil3s----y`, `Vmip1p`, `Vmip1p----y`, `Vmip1s`, `Vmip1s----y`, `Vmip2p`, `Vmip2s`, `Vmip2s----y`, `Vmip3`, `Vmip3-----y`, `Vmip3p`, `Vmip3s`, `Vmip3s----y`, `Vmis1p`, `Vmis1s`, `Vmis3p`, `Vmis3p----y`, `Vmis3s`, `Vmis3s----y`, `Vmm-2p`, `Vmm-2s`, `Vmnp`, `Vmnp------y`, `Vmp--pf`, `Vmp--pm`, `Vmp--sf`, `Vmp--sm`, `Vmp--sm---y`, `Vmsp1p`, `Vmsp2p`, `Vmsp2s`, `Vmsp3`, `Vmsp3-----y`, `X`, `Y`, `Ya`, `Yn`, `Ynfsoy`, `Ynfsry`, `Ynmsoy`, `Ynmsry`, `Yp`, `Yp,Yn`, `Yp-sr`, `Yr`, `_SP` | | **`parser`** | `ROOT`, `acl`, `advcl`, `advcl:tcl`, `advmod`, `advmod:tmod`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `cc:preconj`, `ccomp`, `ccomp:pmod`, `compound`, `conj`, `cop`, `csubj`, `csubj:pass`, `dep`, `det`, `expl`, `expl:impers`, `expl:pass`, `expl:poss`, `expl:pv`, `fixed`, `flat`, `goeswith`, `iobj`, `mark`, `nmod`, `nmod:tmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `obl:agent`, `obl:pmod`, `orphan`, `parataxis`, `punct`, `vocative`, `xcomp` | | **`ner`** | `DATETIME`, `EVENT`, `FACILITY`, `GPE`, `LANGUAGE`, `LOC`, `MONEY`, `NAT_REL_POL`, `NUMERIC_VALUE`, `ORDINAL`, `ORGANIZATION`, `PERIOD`, `PERSON`, `PRODUCT`, `QUANTITY`, `WORK_OF_ART` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.80 | | `TOKEN_P` | 99.67 | | `TOKEN_R` | 99.57 | | `TOKEN_F` | 99.59 | | `TAG_ACC` | 96.29 | | `SENTS_P` | 96.14 | | `SENTS_R` | 96.01 | | `SENTS_F` | 96.07 | | `DEP_UAS` | 88.56 | | `DEP_LAS` | 83.41 | | `LEMMA_ACC` | 95.32 | | `POS_ACC` | 93.68 | | `MORPH_ACC` | 94.78 | | `MORPH_MICRO_P` | 98.74 | | `MORPH_MICRO_R` | 95.62 | | `MORPH_MICRO_F` | 96.89 | | `ENTS_P` | 74.87 | | `ENTS_R` | 76.22 | | `ENTS_F` | 75.54 |
Kamal99919/PatientData001
Kamal99919
2023-10-10T06:38:20Z
0
0
peft
[ "peft", "arxiv:1910.09700", "base_model:TinyPixel/Llama-2-7B-bf16-sharded", "base_model:adapter:TinyPixel/Llama-2-7B-bf16-sharded", "region:us" ]
null
2023-10-10T06:38:16Z
--- library_name: peft base_model: TinyPixel/Llama-2-7B-bf16-sharded --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Data Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ## Training procedure The following `bitsandbytes` quantization config was used during training: - quant_method: bitsandbytes - load_in_8bit: False - load_in_4bit: True - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: nf4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: bfloat16 ### Framework versions - PEFT 0.6.0.dev0 ## Training procedure The following `bitsandbytes` quantization config was used during training: - quant_method: bitsandbytes - load_in_8bit: False - load_in_4bit: True - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: nf4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: bfloat16 ### Framework versions - PEFT 0.6.0.dev0
spacy/ru_core_news_md
spacy
2023-10-10T06:36:44Z
6
3
spacy
[ "spacy", "token-classification", "ru", "license:mit", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - ru license: mit model-index: - name: ru_core_news_md results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.9438296445 - name: NER Recall type: recall value: 0.9474835886 - name: NER F Score type: f_score value: 0.9456530869 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9882061909 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9882061909 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.972948348 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 2.15295e-05 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.9595456565 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.9474984155 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9985729236 --- ### Details: https://spacy.io/models/ru#ru_core_news_md Russian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer. | Feature | Description | | --- | --- | | **Name** | `ru_core_news_md` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` | | **Components** | `tok2vec`, `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` | | **Vectors** | 500002 keys, 20000 unique vectors (300 dimensions) | | **Sources** | [Nerus](https://github.com/natasha/nerus) (Alexander Kukushkin)<br />[Navec](https://github.com/natasha/navec) (Alexander Kukushkin) | | **License** | `MIT` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (900 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`morphologizer`** | `Case=Nom\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Animacy=Anim\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Acc\|POS=NUM`, `Animacy=Inan\|Case=Gen\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=ADP`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET`, `Animacy=Inan\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=NOUN`, `POS=PUNCT`, `Degree=Pos\|POS=ADV`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Mid`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Animacy=Anim\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Aspect=Perf\|Case=Gen\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Animacy=Inan\|Case=Loc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Case=Loc\|Gender=Neut\|Number=Sing\|POS=PRON`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=Third\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Foreign=Yes\|POS=PROPN`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=NUM`, `Aspect=Imp\|Gender=Neut\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Anim\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `POS=NUM`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=Third`, `Aspect=Imp\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Anim\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Dat\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=DET`, `Animacy=Inan\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Dat\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Animacy=Inan\|Case=Dat\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `POS=SCONJ`, `Animacy=Inan\|Case=Ins\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=Third`, `Case=Acc\|POS=NUM`, `Case=Ins\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=NOUN`, `POS=CCONJ`, `Case=Nom\|POS=NUM`, `Animacy=Inan\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Gender=Masc\|Number=Sing\|POS=VERB\|StyleVariant=Short\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Ins\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=Third\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET`, `Aspect=Imp\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=Third\|Tense=Pres\|VerbForm=Fin\|Voice=Mid`, `Case=Ins\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Animacy=Anim\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Dat\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Dat\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Nom\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Degree=Pos\|Number=Plur\|POS=ADJ\|StyleVariant=Short`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Animacy=Inan\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Loc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Perf\|Number=Plur\|POS=VERB\|StyleVariant=Short\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|POS=NUM`, `Animacy=Anim\|Case=Gen\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Animacy=Anim\|Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Mood=Cnd\|POS=SCONJ`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=Third`, `POS=PART\|Polarity=Neg`, `Aspect=Imp\|POS=VERB\|VerbForm=Inf\|Voice=Mid`, `Animacy=Inan\|Aspect=Perf\|Case=Acc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Acc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `POS=SPACE`, `Case=Nom\|Number=Plur\|POS=DET`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Gender=Neut\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Mid`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Animacy=Anim\|Case=Acc\|Number=Plur\|POS=PRON`, `Animacy=Inan\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Anim\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Anim\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `POS=INTJ`, `Animacy=Inan\|Case=Loc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON`, `Aspect=Imp\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=Third`, `Case=Nom\|Number=Plur\|POS=PRON`, `Aspect=Imp\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Mid`, `Aspect=Imp\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|StyleVariant=Short`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=Third`, `Case=Gen\|POS=PRON`, `Animacy=Inan\|Case=Dat\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Animacy=Anim\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|POS=VERB\|VerbForm=Inf\|Voice=Act`, `Animacy=Anim\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=Third`, `Animacy=Inan\|Case=Acc\|Number=Plur\|POS=DET`, `Case=Nom\|POS=PRON`, `Animacy=Anim\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=NOUN`, `POS=ADJ`, `Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=Third\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=Third`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=DET`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Loc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=First`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=First\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Mood=Cnd\|POS=AUX`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=First`, `Case=Gen\|Number=Plur\|POS=DET`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Ins\|Gender=Neut\|Number=Sing\|POS=PRON`, `Aspect=Perf\|POS=VERB\|VerbForm=Inf\|Voice=Mid`, `Aspect=Perf\|Case=Gen\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET`, `POS=PART`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=DET`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=Third\|Tense=Fut\|VerbForm=Fin\|Voice=Mid`, `Aspect=Perf\|Gender=Masc\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Mid`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=NUM`, `Animacy=Anim\|Case=Dat\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=Third\|Tense=Fut\|VerbForm=Fin\|Voice=Mid`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET`, `Aspect=Perf\|Gender=Neut\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|StyleVariant=Short`, `Animacy=Inan\|Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Animacy=Anim\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=Third`, `Aspect=Perf\|Gender=Neut\|Number=Sing\|POS=VERB\|StyleVariant=Short\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Loc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=Third\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Mid`, `Animacy=Inan\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON`, `Aspect=Perf\|Case=Loc\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Loc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Dat\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Animacy=Inan\|Case=Acc\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Foreign=Yes\|POS=X`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|POS=VERB\|Tense=Pres\|VerbForm=Conv\|Voice=Act`, `Case=Gen\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Animacy=Inan\|Case=Ins\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Gender=Neut\|Mood=Ind\|Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Nom\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Gen\|POS=NUM`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|POS=NUM`, `Aspect=Imp\|Case=Gen\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Ins\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Case=Ins\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Case=Nom\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=Third\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Aspect=Imp\|POS=VERB\|VerbForm=Inf\|Voice=Pass`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=NUM`, `Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=Third\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Ins\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=PRON`, `Aspect=Perf\|Gender=Neut\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Mid`, `Animacy=Anim\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Anim\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Case=Acc\|Number=Plur\|POS=PRON\|Person=Third`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON`, `Case=Dat\|POS=PRON`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=Third\|Tense=Pres\|VerbForm=Fin\|Voice=Mid`, `Animacy=Inan\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Case=Nom\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON`, `Case=Ins\|Number=Plur\|POS=PRON\|Person=Third`, `Animacy=Inan\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Case=Dat\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Aspect=Perf\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|POS=AUX\|VerbForm=Inf\|Voice=Act`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=Third\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Imp\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Dat\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|StyleVariant=Short`, `Degree=Cmp\|POS=ADV`, `Aspect=Perf\|Case=Loc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Ins\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Pass`, `Aspect=Perf\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Mid`, `Aspect=Imp\|Gender=Neut\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=AUX\|Person=First\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Ins\|Number=Plur\|POS=DET`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=First\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `Aspect=Imp\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Dat\|Gender=Neut\|Number=Sing\|POS=PRON`, `Case=Loc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Gen\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET`, `Animacy=Inan\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Case=Nom\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Case=Gen\|Gender=Masc\|POS=NUM`, `Animacy=Anim\|Case=Dat\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Case=Ins\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Animacy=Anim\|Case=Ins\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Gender=Fem\|Number=Sing\|POS=VERB\|StyleVariant=Short\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Aspect=Perf\|POS=VERB\|Tense=Past\|VerbForm=Conv\|Voice=Act`, `Aspect=Imp\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET`, `Animacy=Anim\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Dat\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Aspect=Perf\|Case=Loc\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=Second`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET`, `POS=ADV`, `Case=Acc\|POS=PRON`, `Animacy=Anim\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=NUM`, `Case=Ins\|POS=NUM`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=First\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Ins\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET`, `Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Animacy=Anim\|Case=Acc\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=Third`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET`, `Aspect=Perf\|Case=Ins\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|POS=PRON`, `Animacy=Inan\|Case=Acc\|Degree=Pos\|Number=Plur\|POS=DET`, `Animacy=Inan\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=Third`, `Animacy=Anim\|Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=PRON`, `Aspect=Perf\|Case=Ins\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Animacy=Anim\|Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=Second\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=Second`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=Second\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `POS=SYM`, `Degree=Cmp\|POS=ADJ`, `Animacy=Inan\|Case=Dat\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Masc\|POS=NUM`, `Animacy=Inan\|Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Nom\|Gender=Fem\|POS=NUM`, `Animacy=Inan\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Animacy=Anim\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Animacy=Anim\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Aspect=Perf\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Degree=Pos\|POS=ADJ`, `Case=Ins\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Ins\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Animacy=Anim\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Imp\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Pass`, `Case=Gen\|Number=Plur\|POS=PRON\|Person=Third`, `Animacy=Inan\|Case=Acc\|Number=Plur\|POS=PRON`, `Animacy=Anim\|Case=Nom\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Animacy=Anim\|Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Degree=Pos\|Gender=Neut\|Number=Sing\|POS=PUNCT\|StyleVariant=Short`, `Case=Ins\|Degree=Sup\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Pass`, `Animacy=Anim\|Case=Ins\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Animacy=Anim\|Case=Acc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Dat\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Animacy=Anim\|Case=Nom\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Animacy=Anim\|Case=Dat\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=SCONJ`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=PRON`, `Aspect=Imp\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Mid`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=First\|Tense=Pres\|VerbForm=Fin\|Voice=Mid`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=First`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=Second\|Tense=Pres\|VerbForm=Fin\|Voice=Mid`, `POS=NOUN`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=Third`, `Degree=Cmp\|POS=NUM`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=NUM`, `Aspect=Imp\|Case=Nom\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|Number=Plur\|POS=DET`, `Aspect=Perf\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Aspect=Perf\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Dat\|POS=NUM`, `Animacy=Anim\|Aspect=Imp\|Case=Acc\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=Third`, `Animacy=Anim\|Case=Voc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=Third`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=NUM`, `Animacy=Anim\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Animacy=Anim\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Animacy=Inan\|Case=Acc\|Gender=Fem\|POS=NUM`, `Aspect=Perf\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=DET`, `Animacy=Anim\|Case=Gen\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Animacy=Inan\|Case=Par\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Gender=Fem\|Mood=Ind\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Aspect=Perf\|Case=Nom\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON`, `Case=Gen\|Number=Plur\|POS=DET\|Person=Third`, `Animacy=Inan\|Case=Dat\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=ADV`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=NUM`, `Aspect=Perf\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Gender=Masc\|POS=NUM`, `Aspect=Imp\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=Third`, `Animacy=Anim\|Case=Ins\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Animacy=Inan\|Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Gen\|Gender=Fem\|POS=NUM`, `Animacy=Anim\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `POS=ADV\|Polarity=Neg`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PRON`, `Aspect=Perf\|Case=Nom\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Case=Acc\|Gender=Neut\|POS=NUM`, `Aspect=Imp\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=Second\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Number=Sing\|POS=PRON\|Person=First`, `Case=Nom\|Gender=Neut\|POS=NUM`, `Case=Gen\|POS=VERB\|Polarity=Neg`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=Second\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON`, `Aspect=Imp\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Number=Plur\|POS=PRON`, `Case=Loc\|Number=Plur\|POS=PRON\|Person=Third`, `Case=Gen\|Number=Plur\|POS=PRON`, `Aspect=Perf\|Case=Dat\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=NUM`, `Aspect=Imp\|Case=Dat\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `POS=CCONJ\|Polarity=Neg`, `Animacy=Inan\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Gen\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Pass`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=Third`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET`, `Aspect=Imp\|Gender=Neut\|Mood=Ind\|Number=Sing\|POS=PRON\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Aspect=Imp\|POS=VERB\|Tense=Pres\|VerbForm=Conv\|Voice=Mid`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=Second`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=Second\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Animacy=Inan\|Case=Loc\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Aspect=Perf\|Case=Nom\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=Third\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=DET`, `Animacy=Anim\|Case=Acc\|POS=NUM`, `Aspect=Imp\|Number=Plur\|POS=VERB\|StyleVariant=Short\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Gender=Masc\|Number=Sing\|POS=VERB\|StyleVariant=Short\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=Third`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=NUM`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=NUM`, `Aspect=Imp\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Animacy=Anim\|Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Loc\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Gen\|Number=Plur\|POS=PRON\|Person=First`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=First`, `Case=Gen\|Number=Plur\|POS=PRON\|Person=Second`, `Aspect=Perf\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=Second\|VerbForm=Fin\|Voice=Act`, `Aspect=Perf\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=First`, `Foreign=Yes\|POS=PUNCT`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=PRON\|Person=Third\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=AUX\|Person=First\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|Person=Third`, `Case=Dat\|Degree=Sup\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Case=Acc\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Aspect=Perf\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Case=Loc\|POS=NUM`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=First\|Tense=Pres\|VerbForm=Fin\|Voice=Mid`, `Case=Dat\|Number=Plur\|POS=DET`, `Aspect=Imp\|POS=AUX\|Tense=Pres\|VerbForm=Conv\|Voice=Act`, `Aspect=Perf\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Case=Ins\|POS=PRON`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=PRON`, `Aspect=Perf\|Case=Loc\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=Third`, `Aspect=Imp\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=Second\|VerbForm=Fin\|Voice=Mid`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON`, `Animacy=Inan\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `POS=PROPN`, `Aspect=Perf\|Case=Loc\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Pass`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=Second\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Degree=Sup\|Number=Plur\|POS=ADJ`, `Animacy=Anim\|Case=Ins\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Animacy=Inan\|Case=Ins\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Ins\|Number=Plur\|POS=PRON\|Person=Second`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=Third`, `Animacy=Anim\|Case=Loc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Aspect=Imp\|Case=Acc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Dat\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Pass`, `Case=Ins\|Number=Sing\|POS=PRON\|Person=First`, `Aspect=Imp\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Loc\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=DET`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|Person=Third`, `Aspect=Imp\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Aspect=Imp\|Case=Gen\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=NUM`, `Animacy=Inan\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=PUNCT`, `Animacy=Anim\|Case=Dat\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Aspect=Imp\|Case=Ins\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Loc\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=PRON`, `Animacy=Anim\|Aspect=Imp\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Case=Ins\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON`, `Animacy=Inan\|Case=Acc\|Number=Plur\|POS=PRON\|Person=First`, `Animacy=Anim\|Aspect=Perf\|Case=Acc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Aspect=Imp\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Aspect=Imp\|Case=Acc\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Animacy=Anim\|Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Ins\|Number=Sing\|POS=PRON\|Person=Second`, `Aspect=Perf\|Case=Dat\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=DET`, `Animacy=Anim\|Aspect=Perf\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON`, `Aspect=Perf\|Case=Dat\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Case=Nom\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Case=Acc\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Aspect=Imp\|Case=Loc\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Pass`, `Case=Dat\|Number=Plur\|POS=PRON`, `Animacy=Inan\|Case=Ins\|Gender=Neut\|Number=Plur\|POS=PROPN`, `Animacy=Anim\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Animacy=Anim\|Case=Gen\|Number=Plur\|POS=DET`, `Aspect=Perf\|Case=Gen\|Gender=Fem\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Ins\|Degree=Sup\|Number=Plur\|POS=ADJ`, `Case=Ins\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=DET`, `Case=Dat\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Anim\|Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADV`, `Foreign=Yes\|POS=PART`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=First\|Tense=Fut\|VerbForm=Fin\|Voice=Act`, `Case=Gen\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Animacy=Inan\|Aspect=Imp\|Case=Acc\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Case=Dat\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=DET`, `Case=Loc\|Gender=Fem\|POS=NUM`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET`, `Aspect=Perf\|POS=VERB\|Tense=Past\|VerbForm=Conv\|Voice=Mid`, `Aspect=Imp\|Case=Loc\|Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Gen\|Gender=Masc\|Number=Sing\|POS=PUNCT`, `Animacy=Anim\|Case=Loc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Aspect=Perf\|Case=Ins\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=DET`, `Aspect=Perf\|Case=Ins\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET`, `Animacy=Anim\|Aspect=Imp\|Case=Acc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=Third`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=PUNCT`, `Aspect=Imp\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Animacy=Anim\|Case=Loc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Aspect=Perf\|Case=Nom\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Pass`, `Animacy=Inan\|Aspect=Perf\|Case=Acc\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Animacy=Inan\|Case=Ins\|Gender=Fem\|Number=Sing\|POS=ADV`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=DET`, `Aspect=Imp\|Case=Loc\|Gender=Masc\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part\|Voice=Act`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=First\|Tense=Fut\|VerbForm=Fin\|Voice=Mid`, `Case=Nom\|Degree=Sup\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=Second\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=DET`, `Case=Loc\|Number=Sing\|POS=PRON\|Person=First`, _(truncated: full list in pipeline meta)_ | | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `ccomp`, `compound`, `conj`, `cop`, `csubj`, `csubj:pass`, `dep`, `det`, `discourse`, `expl`, `fixed`, `flat`, `flat:foreign`, `flat:name`, `iobj`, `list`, `mark`, `nmod`, `nsubj`, `nsubj:pass`, `nummod`, `nummod:entity`, `nummod:gov`, `obj`, `obl`, `obl:agent`, `orphan`, `parataxis`, `punct`, `xcomp` | | **`ner`** | `LOC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.68 | | `TOKEN_P` | 97.28 | | `TOKEN_R` | 98.31 | | `TOKEN_F` | 97.79 | | `POS_ACC` | 98.82 | | `MORPH_ACC` | 97.29 | | `MORPH_MICRO_P` | 98.88 | | `MORPH_MICRO_R` | 98.17 | | `MORPH_MICRO_F` | 98.52 | | `SENTS_P` | 99.87 | | `SENTS_R` | 99.85 | | `SENTS_F` | 99.86 | | `DEP_UAS` | 95.95 | | `DEP_LAS` | 94.75 | | `TAG_ACC` | 98.82 | | `LEMMA_ACC` | 0.00 | | `ENTS_P` | 94.38 | | `ENTS_R` | 94.75 | | `ENTS_F` | 94.57 |
spacy/sl_core_news_md
spacy
2023-10-10T06:36:15Z
0
0
spacy
[ "spacy", "token-classification", "sl", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2023-07-07T09:07:12Z
--- tags: - spacy - token-classification language: - sl license: cc-by-sa-4.0 model-index: - name: sl_core_news_md results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7239263804 - name: NER Recall type: recall value: 0.746835443 - name: NER F Score type: f_score value: 0.7352024922 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9204829576 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9756170531 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9238593867 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9579655946 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8734121577 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.8430838205 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9008654603 --- ### Details: https://spacy.io/models/sl#sl_core_news_md Slovenian pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), attribute_ruler, senter, ner. | Feature | Description | | --- | --- | | **Name** | `sl_core_news_md` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | floret (50000, 300) | | **Sources** | [UD Slovenian SSJ v2.11](https://github.com/UniversalDependencies/UD_Slovenian-SSJ) (Dobrovoljc, Kaja; Erjavec, Tomaž; Krek, Simon)<br />[Training corpus SUK 1.0](https://www.clarin.si/repository/xmlui/handle/11356/1747) (Arhar Holdt, Špela; Krek, Simon; Dobrovoljc, Kaja; Erjavec, Tomaž; Gantar, Polona; Čibej, Jaka; Pori, Eva; Terčon, Luka; Munda, Tina; Žitnik, Slavko; Robida, Nejc; Blagus, Neli; Može, Sara; Ledinek, Nina; Holz, Nanika; Zupan, Katja; Kuzman, Taja; Kavčič, Teja; Škrjanec, Iza; Marko, Dafne; Jezeršek, Lucija; Zajc, Anja)<br />[Explosion Vectors (OSCAR 2109 + Wikipedia + OpenSubtitles + WMT News Crawl)](https://github.com/explosion/spacy-vectors-builder) (Explosion) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (2401 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `Agcfdn`, `Agcfpa`, `Agcfpd`, `Agcfpg`, `Agcfpi`, `Agcfpl`, `Agcfpn`, `Agcfsa`, `Agcfsd`, `Agcfsg`, `Agcfsi`, `Agcfsl`, `Agcfsn`, `Agcmda`, `Agcmdn`, `Agcmpa`, `Agcmpd`, `Agcmpg`, `Agcmpi`, `Agcmpl`, `Agcmpn`, `Agcmsay`, `Agcmsd`, `Agcmsg`, `Agcmsi`, `Agcmsl`, `Agcmsny`, `Agcndn`, `Agcnpa`, `Agcnpd`, `Agcnpg`, `Agcnpi`, `Agcnpl`, `Agcnpn`, `Agcnsa`, `Agcnsd`, `Agcnsg`, `Agcnsi`, `Agcnsl`, `Agcnsn`, `Agpfda`, `Agpfdg`, `Agpfdi`, `Agpfdl`, `Agpfdn`, `Agpfpa`, `Agpfpd`, `Agpfpg`, `Agpfpi`, `Agpfpl`, `Agpfpn`, `Agpfsa`, `Agpfsd`, `Agpfsg`, `Agpfsi`, `Agpfsl`, `Agpfsn`, `Agpmda`, `Agpmdd`, `Agpmdg`, `Agpmdi`, `Agpmdl`, `Agpmdn`, `Agpmpa`, `Agpmpd`, `Agpmpg`, `Agpmpi`, `Agpmpl`, `Agpmpn`, `Agpmsa`, `Agpmsan`, `Agpmsay`, `Agpmsd`, `Agpmsg`, `Agpmsi`, `Agpmsl`, `Agpmsnn`, `Agpmsny`, `Agpnda`, `Agpndg`, `Agpndi`, `Agpndn`, `Agpnpa`, `Agpnpd`, `Agpnpg`, `Agpnpi`, `Agpnpl`, `Agpnpn`, `Agpnsa`, `Agpnsd`, `Agpnsg`, `Agpnsi`, `Agpnsl`, `Agpnsn`, `Agsfda`, `Agsfpa`, `Agsfpg`, `Agsfpi`, `Agsfpl`, `Agsfpn`, `Agsfsa`, `Agsfsd`, `Agsfsg`, `Agsfsi`, `Agsfsl`, `Agsfsn`, `Agsmdn`, `Agsmpa`, `Agsmpd`, `Agsmpg`, `Agsmpi`, `Agsmpl`, `Agsmpn`, `Agsmsa`, `Agsmsay`, `Agsmsg`, `Agsmsi`, `Agsmsl`, `Agsmsny`, `Agsnpa`, `Agsnpg`, `Agsnpn`, `Agsnsa`, `Agsnsg`, `Agsnsi`, `Agsnsl`, `Agsnsn`, `Appfda`, `Appfdg`, `Appfdi`, `Appfdn`, `Appfpa`, `Appfpd`, `Appfpg`, `Appfpi`, `Appfpl`, `Appfpn`, `Appfsa`, `Appfsd`, `Appfsg`, `Appfsi`, `Appfsl`, `Appfsn`, `Appmda`, `Appmdg`, `Appmdl`, `Appmdn`, `Appmpa`, `Appmpd`, `Appmpg`, `Appmpi`, `Appmpl`, `Appmpn`, `Appmsa`, `Appmsan`, `Appmsay`, `Appmsd`, `Appmsg`, `Appmsi`, `Appmsl`, `Appmsnn`, `Appmsny`, `Appndg`, `Appndn`, `Appnpa`, `Appnpg`, `Appnpi`, `Appnpl`, `Appnpn`, `Appnsa`, `Appnsd`, `Appnsg`, `Appnsi`, `Appnsl`, `Appnsn`, `Aspfdi`, `Aspfdn`, `Aspfpa`, `Aspfpg`, `Aspfpl`, `Aspfpn`, `Aspfsa`, `Aspfsd`, `Aspfsg`, `Aspfsi`, `Aspfsl`, `Aspfsn`, `Aspmdl`, `Aspmdn`, `Aspmpa`, `Aspmpd`, `Aspmpg`, `Aspmpl`, `Aspmpn`, `Aspmsa`, `Aspmsan`, `Aspmsd`, `Aspmsg`, `Aspmsi`, `Aspmsl`, `Aspmsnn`, `Aspnpa`, `Aspnpg`, `Aspnpi`, `Aspnpl`, `Aspnpn`, `Aspnsa`, `Aspnsg`, `Aspnsi`, `Aspnsl`, `Aspnsn`, `Cc`, `Cs`, `I`, `Mdc`, `Mdo`, `Mlc-pa`, `Mlc-pd`, `Mlc-pg`, `Mlc-pi`, `Mlc-pl`, `Mlc-pn`, `Mlcfda`, `Mlcfdg`, `Mlcfdi`, `Mlcfdl`, `Mlcfdn`, `Mlcfpa`, `Mlcfpd`, `Mlcfpg`, `Mlcfpi`, `Mlcfpl`, `Mlcfpn`, `Mlcmda`, `Mlcmdg`, `Mlcmdi`, `Mlcmdl`, `Mlcmdn`, `Mlcmpa`, `Mlcmpd`, `Mlcmpg`, `Mlcmpi`, `Mlcmpl`, `Mlcmpn`, `Mlcnda`, `Mlcndg`, `Mlcndi`, `Mlcndl`, `Mlcndn`, `Mlcnpa`, `Mlcnpg`, `Mlcnpi`, `Mlcnpl`, `Mlcnpn`, `Mlofpa`, `Mlofpd`, `Mlofpg`, `Mlofpi`, `Mlofpl`, `Mlofpn`, `Mlofsa`, `Mlofsd`, `Mlofsg`, `Mlofsi`, `Mlofsl`, `Mlofsn`, `Mlompa`, `Mlompg`, `Mlompi`, `Mlompl`, `Mlompn`, `Mlomsa`, `Mlomsd`, `Mlomsg`, `Mlomsi`, `Mlomsl`, `Mlomsn`, `Mlonda`, `Mlonpg`, `Mlonpl`, `Mlonpn`, `Mlonsa`, `Mlonsg`, `Mlonsi`, `Mlonsl`, `Mlonsn`, `Mlpfdl`, `Mlpfdn`, `Mlpfpa`, `Mlpfpg`, `Mlpfpi`, `Mlpfpl`, `Mlpfpn`, `Mlpfsa`, `Mlpfsd`, `Mlpfsg`, `Mlpfsi`, `Mlpfsl`, `Mlpfsn`, `Mlpmdl`, `Mlpmpa`, `Mlpmpd`, `Mlpmpg`, `Mlpmpi`, `Mlpmpl`, `Mlpmpn`, `Mlpmsa`, `Mlpmsan`, `Mlpmsay`, `Mlpmsd`, `Mlpmsg`, `Mlpmsi`, `Mlpmsl`, `Mlpmsn`, `Mlpmsnn`, `Mlpmsny`, `Mlpnpa`, `Mlpnpg`, `Mlpnpi`, `Mlpnpl`, `Mlpnpn`, `Mlpnsa`, `Mlpnsg`, `Mlpnsi`, `Mlpnsl`, `Mlpnsn`, `Mlsfpa`, `Mlsfsg`, `Mlsfsi`, `Mlsfsn`, `Mlsmpi`, `Mlsmsg`, `Mlsmsi`, `Mlsnsa`, `Mlsnsi`, `Mlsnsn`, `Mrc`, `Mro`, `Ncfda`, `Ncfdd`, `Ncfdg`, `Ncfdi`, `Ncfdl`, `Ncfdn`, `Ncfpa`, `Ncfpd`, `Ncfpg`, `Ncfpi`, `Ncfpl`, `Ncfpn`, `Ncfsa`, `Ncfsd`, `Ncfsg`, `Ncfsi`, `Ncfsl`, `Ncfsn`, `Ncmda`, `Ncmdd`, `Ncmdg`, `Ncmdi`, `Ncmdl`, `Ncmdn`, `Ncmpa`, `Ncmpd`, `Ncmpg`, `Ncmpi`, `Ncmpl`, `Ncmpn`, `Ncmsan`, `Ncmsay`, `Ncmsd`, `Ncmsg`, `Ncmsi`, `Ncmsl`, `Ncmsn`, `Ncnda`, `Ncndd`, `Ncndg`, `Ncndi`, `Ncndl`, `Ncndn`, `Ncnpa`, `Ncnpd`, `Ncnpg`, `Ncnpi`, `Ncnpl`, `Ncnpn`, `Ncnsa`, `Ncnsd`, `Ncnsg`, `Ncnsi`, `Ncnsl`, `Ncnsn`, `Npfpa`, `Npfpd`, `Npfpg`, `Npfpi`, `Npfpl`, `Npfpn`, `Npfsa`, `Npfsd`, `Npfsg`, `Npfsi`, `Npfsl`, `Npfsn`, `Npmda`, `Npmdg`, `Npmdn`, `Npmpa`, `Npmpd`, `Npmpg`, `Npmpi`, `Npmpl`, `Npmpn`, `Npmsan`, `Npmsay`, `Npmsd`, `Npmsg`, `Npmsi`, `Npmsl`, `Npmsn`, `Npnpn`, `Npnsa`, `Npnsd`, `Npnsg`, `Npnsi`, `Npnsl`, `Npnsn`, `Pd-fda`, `Pd-fpa`, `Pd-fpd`, `Pd-fpg`, `Pd-fpi`, `Pd-fpl`, `Pd-fpn`, `Pd-fsa`, `Pd-fsd`, `Pd-fsg`, `Pd-fsi`, `Pd-fsl`, `Pd-fsn`, `Pd-mda`, `Pd-mdg`, `Pd-mdi`, `Pd-mdl`, `Pd-mdn`, `Pd-mpa`, `Pd-mpd`, `Pd-mpg`, `Pd-mpi`, `Pd-mpl`, `Pd-mpn`, `Pd-msa`, `Pd-msd`, `Pd-msg`, `Pd-msi`, `Pd-msl`, `Pd-msn`, `Pd-npa`, `Pd-npd`, `Pd-npg`, `Pd-npi`, `Pd-npl`, `Pd-npn`, `Pd-nsa`, `Pd-nsd`, `Pd-nsg`, `Pd-nsi`, `Pd-nsl`, `Pd-nsn`, `Pg-fda`, `Pg-fdg`, `Pg-fdi`, `Pg-fdl`, `Pg-fdn`, `Pg-fpa`, `Pg-fpd`, `Pg-fpg`, `Pg-fpi`, `Pg-fpl`, `Pg-fpn`, `Pg-fsa`, `Pg-fsd`, `Pg-fsg`, `Pg-fsi`, `Pg-fsl`, `Pg-fsn`, `Pg-mda`, `Pg-mdd`, `Pg-mdg`, `Pg-mdi`, `Pg-mdl`, `Pg-mdn`, `Pg-mpa`, `Pg-mpd`, `Pg-mpg`, `Pg-mpi`, `Pg-mpl`, `Pg-mpn`, `Pg-msa`, _(truncated: full list in pipeline meta)_ | | **`morphologizer`** | `POS=PUNCT`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `POS=DET\|PronType=Ind`, `Aspect=Perf\|Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part`, `Aspect=Perf\|Gender=Neut\|Number=Sing\|POS=VERB\|VerbForm=Part`, `POS=PRON\|PronType=Prs\|Reflex=Yes\|Variant=Short`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Loc\|POS=ADP`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `POS=SCONJ`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs\|Variant=Short`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Gender=Fem\|Number=Sing\|POS=AUX\|VerbForm=Part`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `POS=VERB\|VerbForm=Inf`, `Mood=Cnd\|POS=AUX\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Short`, `Case=Gen\|POS=ADP`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=CCONJ`, `Aspect=Perf\|Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `POS=PART`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|POS=ADP`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Ins\|POS=ADP`, `Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `Aspect=Perf\|Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Aspect=Imp\|Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part`, `Degree=Pos\|POS=ADV`, `Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Polarity=Pos\|Tense=Fut\|VerbForm=Fin`, `Aspect=Perf\|Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Polarity=Pos\|Tense=Fut\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Perf\|POS=VERB\|VerbForm=Inf`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int`, `Gender=Neut\|Number=Sing\|POS=AUX\|VerbForm=Part`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Short`, `Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Short`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Gen\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Rel`, `Degree=Cmp\|POS=ADV`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Ins\|Gender=Fem\|Number=Plur\|POS=NOUN`, `Degree=Sup\|POS=ADV`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Dem`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Dat\|POS=ADP`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Short`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Ins\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Acc\|Gender=Fem\|Number=Dual\|POS=DET\|PronType=Tot`, `Case=Acc\|Gender=Fem\|Number=Dual\|POS=NOUN`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Ins\|Gender=Masc\|Number=Dual\|POS=DET\|PronType=Tot`, `Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Dual\|POS=ADJ`, `Case=Ins\|Gender=Masc\|Number=Dual\|POS=NOUN`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Ins\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=NOUN`, `Case=Ins\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part`, `Case=Loc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Ins\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part`, `Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Gender[psor]=Masc\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Aspect=Imp\|Gender=Neut\|Number=Sing\|POS=VERB\|VerbForm=Part`, `POS=AUX\|VerbForm=Inf`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Acc\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `POS=PART\|Polarity=Neg`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Neg`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Polarity=Pos\|Tense=Fut\|VerbForm=Fin`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Aspect=Perf\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin`, `Aspect=Imp\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=2\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Bound`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=2\|Polarity=Pos\|Tense=Fut\|VerbForm=Fin`, `Case=Loc\|POS=PRON\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Gen\|Gender=Fem\|NumForm=Word\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|NumForm=Word\|NumType=Card\|Number=Dual\|POS=NUM`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=3\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `NumForm=Digit\|NumType=Card\|POS=NUM`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Neg`, `Case=Nom\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Aspect=Imp\|Gender=Fem\|Number=Sing\|POS=VERB\|VerbForm=Part`, `Case=Ins\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Ins\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Gender=Masc\|Number=Plur\|POS=AUX\|VerbForm=Part`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ\|VerbForm=Part`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Aspect=Imp\|Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part`, `NumForm=Roman\|NumType=Ord\|POS=NUM`, `Gender=Masc\|Number=Sing\|POS=VERB\|VerbForm=Part`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Mood=Ind\|Number=Dual\|POS=AUX\|Person=3\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `Gender=Fem\|Number=Dual\|POS=VERB\|VerbForm=Part`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Short`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=3\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|NumForm=Word\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=NOUN`, `POS=X`, `POS=SYM`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Dual\|POS=ADJ`, `Case=Nom\|Gender=Masc\|Number=Dual\|POS=NOUN`, `Aspect=Perf\|Gender=Masc\|Number=Dual\|POS=VERB\|VerbForm=Part`, `Animacy=Anim\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Abbr=Yes\|POS=X`, `Aspect=Perf\|Mood=Ind\|Number=Dual\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Dem`, `Gender=Masc\|Number=Dual\|POS=AUX\|VerbForm=Part`, `Case=Dat\|POS=PRON\|PronType=Prs\|Reflex=Yes\|Variant=Short`, `Aspect=Imp\|Gender=Masc\|Number=Dual\|POS=VERB\|VerbForm=Part`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Acc\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Ins\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Ins\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Acc\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Short`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Short`, `Gender=Masc\|Number=Sing\|POS=AUX\|VerbForm=Part`, `Case=Dat\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs\|Variant=Short`, `Case=Gen\|Gender=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Neut\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Aspect=Imp\|Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Short`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Short`, `Case=Loc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ins\|NumForm=Word\|NumType=Card\|Number=Plur\|POS=NUM`, `NumForm=Digit\|NumType=Ord\|POS=NUM`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Nom\|NumForm=Word\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|NumForm=Word\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Nom\|Gender=Masc\|NumForm=Word\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Gender=Masc\|Number=Plur\|POS=VERB\|VerbForm=Part`, `Case=Dat\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Bound`, `Case=Gen\|Gender=Masc\|NumForm=Word\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Mood=Ind\|Number=Dual\|POS=VERB\|Person=3\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `POS=SPACE`, `Aspect=Imp\|POS=VERB\|VerbForm=Inf`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Loc\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Sup\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Short`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Dem`, `Gender=Neut\|Number=Sing\|POS=VERB\|VerbForm=Part`, `Case=Gen\|Gender=Masc\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Rel`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `POS=DET\|PronType=Int`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Int`, `Case=Nom\|Gender=Neut\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Masc\|Number=Plur\|Number[psor]=Dual\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Dual\|POS=AUX\|Person=2\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Short`, `Case=Nom\|Gender=Masc\|Number=Dual\|POS=DET\|PronType=Tot`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Gender[psor]=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Gen\|Gender=Neut\|Number=Sing\|Number[psor]=Dual\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Neg`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `Case=Ins\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Gen\|Gender=Masc\|Gender[psor]=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Case=Nom\|Gender=Masc\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Masc\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Aspect=Imp\|Mood=Ind\|Number=Dual\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin`, `Case=Gen\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Aspect=Imp\|POS=VERB\|VerbForm=Sup`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Ind`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Int`, `Case=Acc\|Gender=Neut\|NumForm=Word\|NumType=Card\|Number=Plur\|POS=NUM`, `Gender=Neut\|Number=Plur\|POS=AUX\|VerbForm=Part`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Acc\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|Gender=Fem\|NumForm=Word\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Loc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Case=Loc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Bound`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs\|Variant=Bound`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Neg`, `Case=Acc\|POS=PRON\|PronType=Prs\|Reflex=Yes\|Variant=Bound`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Dual\|POS=NOUN`, `Mood=Ind\|Number=Sing\|POS=AUX\|Person=1\|Polarity=Pos\|Tense=Fut\|VerbForm=Fin`, `Case=Ins\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Short`, `Aspect=Imp\|Mood=Ind\|Number=Dual\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `POS=INTJ`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Aspect=Perf\|POS=VERB\|VerbForm=Sup`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Foreign=Yes\|POS=X`, `Case=Nom\|Gender=Fem\|Gender[psor]=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Gender=Neut\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Sup\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Gender[psor]=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Loc\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Nom\|Gender=Masc\|NumForm=Word\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Acc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Loc\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Aspect=Perf\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|VerbForm=Fin`, `Aspect=Perf\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Sing\|POS=VERB\|Person=2\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Fem\|NumForm=Word\|NumType=Card\|Number=Plur\|POS=NUM`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|VerbForm=Part`, `Mood=Ind\|Number=Plur\|POS=AUX\|Person=1\|Polarity=Pos\|Tense=Fut\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Nom\|Definite=Def\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Masc\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Dual\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Int`, `Gender=Fem\|Number=Plur\|POS=VERB\|VerbForm=Part`, `Aspect=Imp\|Mood=Imp\|Number=Sing\|POS=VERB\|Person=2\|VerbForm=Fin`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Loc\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Loc\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Neg`, `Case=Nom\|Gender=Masc\|NumForm=Word\|NumType=Card\|Number=Dual\|POS=NUM`, `Case=Nom\|Degree=Pos\|Gender=Masc\|Number=Dual\|POS=ADJ\|VerbForm=Part`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Aspect=Perf\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Case=Acc\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Tot`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Polarity=Pos\|Tense=Fut\|VerbForm=Fin`, `Case=Acc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ\|Poss=Yes`, `Case=Nom\|Gender=Fem\|Number=Dual\|POS=NOUN`, `Case=Gen\|Gender=Masc\|NumForm=Word\|NumType=Card\|Number=Dual\|POS=NUM`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Dual\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Number=Dual\|POS=DET\|PronType=Tot`, `Case=Gen\|Gender=Masc\|Number=Dual\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Gen\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Animacy=Inan\|Case=Acc\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=DET\|PronType=Ind`, `Gender=Fem\|Number=Plur\|POS=AUX\|VerbForm=Part`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Dat\|Gender=Fem\|Number=Plur\|POS=NOUN`, `NumForm=Roman\|NumType=Card\|POS=NUM`, `Case=Loc\|Gender=Fem\|NumForm=Word\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Rel`, `Case=Acc\|Gender=Masc\|NumForm=Word\|NumType=Card\|Number=Dual\|POS=NUM`, `Case=Acc\|Degree=Pos\|Gender=Masc\|Number=Dual\|POS=ADJ`, `Case=Acc\|Gender=Masc\|Number=Dual\|POS=NOUN`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Loc\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Int`, `Case=Gen\|Gender=Neut\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Gender[psor]=Masc\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Loc\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Loc\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Acc\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Loc\|Gender=Masc\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Ins\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Gen\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Nom\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Gen\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Ins\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Aspect=Perf\|Gender=Neut\|Number=Plur\|POS=VERB\|VerbForm=Part`, `Case=Gen\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Fem\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=PROPN`, `Case=Dat\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Loc\|Gender=Fem\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|Number=Sing\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Neut\|Gender[psor]=Masc\|Number=Sing\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Dat\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ\|VerbForm=Part`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Tot`, `Aspect=Imp\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=2\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Degree=Cmp\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Fem\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Masc\|Gender[psor]=Fem\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Neg`, `Case=Nom\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Dat\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Nom\|Gender=Masc\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Case=Nom\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Dat\|Degree=Pos\|Gender=Neut\|Number=Plur\|POS=ADJ`, `Case=Dat\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Case=Gen\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Gender=Neut\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Gen\|Gender=Masc\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Tot`, `Case=Loc\|Degree=Pos\|Gender=Fem\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Gen\|Gender=Masc\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Case=Dat\|Degree=Pos\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Case=Dat\|Degree=Cmp\|Gender=Fem\|Number=Plur\|POS=ADJ`, `Aspect=Perf\|Mood=Imp\|Number=Plur\|POS=VERB\|Person=1\|VerbForm=Fin`, `Case=Nom\|Degree=Pos\|Gender=Fem\|Number=Dual\|POS=ADJ`, `Aspect=Imp\|Gender=Neut\|Number=Dual\|POS=VERB\|VerbForm=Part`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PROPN`, `Case=Ins\|Gender=Neut\|NumForm=Word\|NumType=Card\|Number=Dual\|POS=NUM`, `Case=Ins\|Gender=Neut\|Number=Dual\|POS=NOUN`, `Case=Nom\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Ins\|Gender=Masc\|Number=Sing\|POS=PROPN`, `Case=Acc\|Gender=Fem\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Case=Gen\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ\|Poss=Yes`, `Case=Nom\|Gender=Fem\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Acc\|Degree=Cmp\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Loc\|Gender=Neut\|NumForm=Word\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Gen\|Degree=Sup\|Gender=Masc\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs\|Variant=Short`, `Case=Nom\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Ind`, `Case=Dat\|Gender=Masc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Dat\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Case=Nom\|Gender=Fem\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Masc\|NumType=Ord\|Number=Plur\|POS=ADJ`, `Case=Acc\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Case=Acc\|Gender=Fem\|Number=Dual\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Gender=Neut\|Number=Sing\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Loc\|Degree=Cmp\|Gender=Fem\|Number=Sing\|POS=ADJ`, `Case=Gen\|Gender=Masc\|Gender[psor]=Masc\|Number=Plur\|Number[psor]=Sing\|POS=DET\|Person=3\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Gender=Fem\|Number=Plur\|POS=DET\|Poss=Yes\|PronType=Prs\|Reflex=Yes`, `Case=Dat\|Number=Dual\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Loc\|Gender=Neut\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Acc\|Definite=Def\|Degree=Cmp\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Case=Acc\|Number=Dual\|POS=PRON\|Person=1\|PronType=Prs`, `Aspect=Perf\|Mood=Ind\|Number=Dual\|POS=VERB\|Person=1\|Tense=Pres\|VerbForm=Fin`, `Mood=Ind\|Number=Dual\|POS=AUX\|Person=1\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `POS=DET\|PronType=Dem`, `Case=Loc\|Gender=Neut\|Number=Plur\|Number[psor]=Plur\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Gen\|Gender=Fem\|Number=Dual\|POS=DET\|PronType=Tot`, `Case=Gen\|Degree=Pos\|Gender=Fem\|Number=Dual\|POS=ADJ`, `Case=Gen\|Gender=Fem\|Number=Dual\|POS=NOUN`, `Case=Ins\|Gender=Masc\|NumType=Ord\|Number=Sing\|POS=ADJ`, `Mood=Ind\|Number=Plur\|POS=VERB\|Person=1\|Polarity=Pos\|Tense=Pres\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Sing\|Number[psor]=Dual\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Aspect=Imp\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Polarity=Neg\|Tense=Pres\|VerbForm=Fin`, `Case=Gen\|Gender=Fem\|Number=Sing\|POS=DET\|PronType=Neg`, `Mood=Ind\|Number=Dual\|POS=AUX\|Person=1\|Polarity=Pos\|Tense=Fut\|VerbForm=Fin`, `Case=Nom\|Gender=Masc\|Number=Plur\|Number[psor]=Dual\|POS=DET\|Person=1\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Gender=Masc\|Number=Dual\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Ins\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Gender=Masc\|Number=Dual\|POS=PROPN`, _(truncated: full list in pipeline meta)_ | | **`parser`** | `ROOT`, `acl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `case`, `cc`, `cc:preconj`, `ccomp`, `conj`, `cop`, `csubj`, `dep`, `det`, `discourse`, `expl`, `fixed`, `flat`, `flat:foreign`, `flat:name`, `iobj`, `list`, `mark`, `nmod`, `nsubj`, `nummod`, `obj`, `obl`, `orphan`, `parataxis`, `punct`, `vocative`, `xcomp` | | **`ner`** | `DERIV_PER`, `LOC`, `MISC`, `ORG`, `PER` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.81 | | `TOKEN_P` | 99.81 | | `TOKEN_R` | 99.57 | | `TOKEN_F` | 99.69 | | `TAG_ACC` | 92.05 | | `POS_ACC` | 97.56 | | `MORPH_ACC` | 92.39 | | `MORPH_MICRO_P` | 95.61 | | `MORPH_MICRO_R` | 95.35 | | `MORPH_MICRO_F` | 95.48 | | `SENTS_P` | 88.62 | | `SENTS_R` | 91.60 | | `SENTS_F` | 90.09 | | `DEP_UAS` | 87.34 | | `DEP_LAS` | 84.31 | | `LEMMA_ACC` | 95.80 | | `ENTS_P` | 72.39 | | `ENTS_R` | 74.68 | | `ENTS_F` | 73.52 |
spacy/sv_core_news_md
spacy
2023-10-10T06:35:45Z
2
1
spacy
[ "spacy", "token-classification", "sv", "license:cc-by-sa-4.0", "model-index", "region:us" ]
token-classification
2022-05-02T07:56:23Z
--- tags: - spacy - token-classification language: - sv license: cc-by-sa-4.0 model-index: - name: sv_core_news_md results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8421624559 - name: NER Recall type: recall value: 0.7542579075 - name: NER F Score type: f_score value: 0.7957900141 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9514136981 - task: name: POS type: token-classification metrics: - name: POS (UPOS) Accuracy type: accuracy value: 0.9628457691 - task: name: MORPH type: token-classification metrics: - name: Morph (UFeats) Accuracy type: accuracy value: 0.9560069409 - task: name: LEMMA type: token-classification metrics: - name: Lemma Accuracy type: accuracy value: 0.9550882923 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.8323804132 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.783130484 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.9269717624 --- ### Details: https://spacy.io/models/sv#sv_core_news_md Swedish pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner. | Feature | Description | | --- | --- | | **Name** | `sv_core_news_md` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | floret (50000, 300) | | **Sources** | [UD Swedish Talbanken v2.8](https://github.com/UniversalDependencies/UD_Swedish-Talbanken) (Nivre, Joakim; Smith, Aaron)<br />[Stockholm-Umeå Corpus (SUC) v3.0](https://huggingface.co/datasets/KBLab/sucx3_ner) (Språkbanken)<br />[Explosion Vectors (OSCAR 2109 + Wikipedia + OpenSubtitles + WMT News Crawl)](https://github.com/explosion/spacy-vectors-builder) (Explosion) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (381 labels for 4 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `AB`, `AB\|AN`, `AB\|KOM`, `AB\|POS`, `AB\|SMS`, `AB\|SUV`, `DT\|NEU\|SIN\|DEF`, `DT\|NEU\|SIN\|IND`, `DT\|NEU\|SIN\|IND/DEF`, `DT\|UTR/NEU\|PLU\|DEF`, `DT\|UTR/NEU\|PLU\|IND`, `DT\|UTR/NEU\|PLU\|IND/DEF`, `DT\|UTR/NEU\|SIN/PLU\|IND`, `DT\|UTR/NEU\|SIN\|DEF`, `DT\|UTR/NEU\|SIN\|IND`, `DT\|UTR\|SIN\|DEF`, `DT\|UTR\|SIN\|IND`, `DT\|UTR\|SIN\|IND/DEF`, `HA`, `HD\|NEU\|SIN\|IND`, `HD\|UTR/NEU\|PLU\|IND`, `HD\|UTR\|SIN\|IND`, `HP\|-\|-\|-`, `HP\|NEU\|SIN\|IND`, `HP\|UTR/NEU\|PLU\|IND`, `HP\|UTR\|SIN\|IND`, `HS\|DEF`, `IE`, `IN`, `JJ`, `JJ\|AN`, `JJ\|KOM\|UTR/NEU\|SIN/PLU\|IND/DEF\|NOM`, `JJ\|POS\|MAS\|SIN\|DEF\|GEN`, `JJ\|POS\|MAS\|SIN\|DEF\|NOM`, `JJ\|POS\|NEU\|SIN\|IND/DEF\|NOM`, `JJ\|POS\|NEU\|SIN\|IND\|NOM`, `JJ\|POS\|UTR/NEU\|PLU\|IND/DEF\|GEN`, `JJ\|POS\|UTR/NEU\|PLU\|IND/DEF\|NOM`, `JJ\|POS\|UTR/NEU\|PLU\|IND\|NOM`, `JJ\|POS\|UTR/NEU\|SIN/PLU\|IND/DEF\|NOM`, `JJ\|POS\|UTR/NEU\|SIN\|DEF\|NOM`, `JJ\|POS\|UTR\|-\|-\|SMS`, `JJ\|POS\|UTR\|SIN\|IND/DEF\|NOM`, `JJ\|POS\|UTR\|SIN\|IND\|GEN`, `JJ\|POS\|UTR\|SIN\|IND\|NOM`, `JJ\|SUV\|MAS\|SIN\|DEF\|NOM`, `JJ\|SUV\|UTR/NEU\|PLU\|DEF\|NOM`, `JJ\|SUV\|UTR/NEU\|SIN/PLU\|DEF\|NOM`, `JJ\|SUV\|UTR/NEU\|SIN/PLU\|IND\|NOM`, `KN`, `MAD`, `MID`, `NN`, `NN\|-\|-\|-\|-`, `NN\|AN`, `NN\|NEU\|-\|-\|SMS`, `NN\|NEU\|PLU\|DEF\|GEN`, `NN\|NEU\|PLU\|DEF\|NOM`, `NN\|NEU\|PLU\|IND\|GEN`, `NN\|NEU\|PLU\|IND\|NOM`, `NN\|NEU\|SIN\|DEF\|GEN`, `NN\|NEU\|SIN\|DEF\|NOM`, `NN\|NEU\|SIN\|IND`, `NN\|NEU\|SIN\|IND\|GEN`, `NN\|NEU\|SIN\|IND\|NOM`, `NN\|SMS`, `NN\|UTR\|-\|-\|-`, `NN\|UTR\|-\|-\|SMS`, `NN\|UTR\|PLU\|DEF\|GEN`, `NN\|UTR\|PLU\|DEF\|NOM`, `NN\|UTR\|PLU\|IND\|GEN`, `NN\|UTR\|PLU\|IND\|NOM`, `NN\|UTR\|SIN\|DEF\|GEN`, `NN\|UTR\|SIN\|DEF\|NOM`, `NN\|UTR\|SIN\|IND\|GEN`, `NN\|UTR\|SIN\|IND\|NOM`, `PAD`, `PC\|PRF\|NEU\|SIN\|IND\|NOM`, `PC\|PRF\|UTR/NEU\|PLU\|IND/DEF\|GEN`, `PC\|PRF\|UTR/NEU\|PLU\|IND/DEF\|NOM`, `PC\|PRF\|UTR/NEU\|SIN\|DEF\|NOM`, `PC\|PRF\|UTR\|SIN\|IND\|NOM`, `PC\|PRS\|UTR/NEU\|SIN/PLU\|IND/DEF\|NOM`, `PL`, `PM`, `PM\|GEN`, `PM\|NOM`, `PM\|SMS`, `PN\|MAS\|SIN\|DEF\|SUB/OBJ`, `PN\|NEU\|SIN\|DEF`, `PN\|NEU\|SIN\|DEF\|SUB/OBJ`, `PN\|NEU\|SIN\|IND\|SUB/OBJ`, `PN\|UTR/NEU\|PLU\|DEF\|OBJ`, `PN\|UTR/NEU\|PLU\|DEF\|SUB`, `PN\|UTR/NEU\|PLU\|DEF\|SUB/OBJ`, `PN\|UTR/NEU\|PLU\|IND\|SUB/OBJ`, `PN\|UTR/NEU\|SIN/PLU\|DEF\|OBJ`, `PN\|UTR\|PLU\|DEF\|OBJ`, `PN\|UTR\|PLU\|DEF\|SUB`, `PN\|UTR\|SIN\|DEF\|NOM`, `PN\|UTR\|SIN\|DEF\|OBJ`, `PN\|UTR\|SIN\|DEF\|SUB`, `PN\|UTR\|SIN\|DEF\|SUB/OBJ`, `PN\|UTR\|SIN\|IND\|NOM`, `PN\|UTR\|SIN\|IND\|SUB`, `PN\|UTR\|SIN\|IND\|SUB/OBJ`, `PP`, `PS\|NEU\|SIN\|DEF`, `PS\|UTR/NEU\|PLU\|DEF`, `PS\|UTR/NEU\|SIN/PLU\|DEF`, `PS\|UTR\|SIN\|DEF`, `RG\|NEU\|SIN\|IND\|NOM`, `RG\|NOM`, `RG\|SMS`, `RG\|UTR\|SIN\|IND\|NOM`, `RO\|MAS\|SIN\|IND/DEF\|NOM`, `RO\|NOM`, `SN`, `UO`, `VB\|AN`, `VB\|IMP\|AKT`, `VB\|IMP\|SFO`, `VB\|INF\|AKT`, `VB\|INF\|SFO`, `VB\|KON\|PRS\|AKT`, `VB\|KON\|PRT\|AKT`, `VB\|PRS\|AKT`, `VB\|PRS\|SFO`, `VB\|PRT\|AKT`, `VB\|PRT\|SFO`, `VB\|SUP\|AKT`, `VB\|SUP\|SFO`, `_SP` | | **`morphologizer`** | `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Com\|Number=Sing\|POS=ADJ`, `Case=Nom\|Definite=Ind\|Gender=Com\|Number=Sing\|POS=NOUN`, `POS=ADP`, `Case=Nom\|Definite=Ind\|Gender=Com\|Number=Plur\|POS=NOUN`, `Case=Nom\|Definite=Def\|Gender=Com\|Number=Sing\|POS=NOUN`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|Voice=Pass`, `POS=PUNCT`, `Definite=Def\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Prs`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Abbr=Yes\|POS=ADV`, `POS=SCONJ`, `POS=ADV`, `Case=Nom\|Definite=Ind\|Gender=Com\|NumType=Card\|Number=Sing\|POS=NUM`, `Mood=Ind\|POS=AUX\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `POS=PART`, `POS=VERB\|VerbForm=Inf`, `Definite=Def\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Prs`, `Number=Plur\|POS=DET\|PronType=Tot`, `Case=Nom\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Nom\|Definite=Ind\|Gender=Neut\|Number=Plur\|POS=NOUN`, `POS=CCONJ`, `Definite=Def\|Number=Plur\|POS=DET\|PronType=Art`, `POS=PRON\|PronType=Rel`, `Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Dem`, `Degree=Pos\|POS=ADV`, `Definite=Def\|Number=Plur\|POS=DET\|PronType=Dem`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Definite=Def\|Gender=Com\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `POS=VERB\|VerbForm=Sup\|Voice=Act`, `Case=Nom\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=PART\|Polarity=Neg`, `Case=Nom\|Degree=Pos\|POS=ADJ`, `Case=Gen\|Definite=Ind\|Gender=Com\|Number=Plur\|POS=NOUN`, `Degree=Cmp\|POS=ADV`, `POS=VERB\|VerbForm=Inf\|Voice=Pass`, `Case=Nom\|Definite=Ind\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Case=Nom\|Definite=Def\|Gender=Com\|Number=Plur\|POS=NOUN`, `Degree=Sup\|POS=ADV`, `Case=Nom\|NumType=Card\|POS=NUM`, `Abbr=Yes\|POS=NOUN`, `Case=Nom\|Definite=Def\|Degree=Sup\|POS=ADJ`, `Case=Gen\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Mood=Imp\|POS=VERB\|VerbForm=Fin\|Voice=Act`, `POS=VERB\|VerbForm=Inf\|Voice=Act`, `Case=Nom\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Mood=Ind\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Case=Gen\|Definite=Ind\|Gender=Neut\|Number=Plur\|POS=NOUN`, `POS=AUX\|VerbForm=Inf\|Voice=Act`, `Case=Nom\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=ADJ\|Tense=Past\|VerbForm=Part`, `Case=Nom\|Definite=Def\|Number=Plur\|POS=PRON\|PronType=Prs`, `Case=Nom\|Number=Plur\|POS=ADJ\|Tense=Past\|VerbForm=Part`, `POS=AUX\|VerbForm=Sup\|Voice=Act`, `Case=Acc\|Definite=Def\|Number=Plur\|POS=PRON\|PronType=Rcp`, `POS=SPACE`, `POS=VERB\|VerbForm=Sup\|Voice=Pass`, `Mood=Ind\|POS=AUX\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Definite=Def\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Nom\|Degree=Cmp\|POS=ADJ`, `Definite=Ind\|Number=Sing\|POS=DET\|PronType=Tot`, `Definite=Ind\|Gender=Com\|Number=Sing\|POS=DET\|PronType=Art`, `Case=Nom\|Definite=Ind\|Gender=Com\|Number=Sing\|POS=ADJ\|Tense=Past\|VerbForm=Part`, `Definite=Ind\|POS=DET\|PronType=Ind`, `Case=Nom\|Definite=Def\|Number=Sing\|POS=ADJ\|Tense=Past\|VerbForm=Part`, `Case=Nom\|POS=ADJ\|Tense=Pres\|VerbForm=Part`, `Definite=Ind\|Gender=Com\|Number=Sing\|POS=DET\|PronType=Ind`, `Definite=Def\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Dem`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Art`, `Mood=Ind\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Definite=Def\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Prs`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Int`, `Definite=Def\|Gender=Com\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Definite=Def\|Gender=Neut\|Number=Sing\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Case=Nom\|Definite=Def\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Prs`, `Definite=Def\|Number=Plur\|POS=PRON\|PronType=Dem`, `Definite=Def\|Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Case=Acc\|Definite=Def\|Number=Plur\|POS=PRON\|PronType=Prs`, `Case=Nom\|Definite=Def\|Degree=Sup\|Number=Plur\|POS=ADJ`, `Case=Nom\|Degree=Pos\|Gender=Com\|Number=Sing\|POS=ADJ`, `Gender=Com\|Number=Sing\|POS=DET\|PronType=Tot`, `Definite=Def\|Gender=Com\|Number=Sing\|POS=DET\|PronType=Dem`, `Case=Gen\|Definite=Ind\|Gender=Com\|Number=Sing\|POS=NOUN`, `POS=NOUN`, `Case=Nom\|POS=ADJ`, `Case=Nom\|Definite=Ind\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Ind`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Definite=Ind\|Number=Plur\|POS=PRON\|PronType=Tot`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Ind`, `Definite=Ind\|Number=Plur\|POS=PRON\|PronType=Ind`, `Definite=Def\|POS=PRON\|Poss=Yes\|PronType=Ind`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Gender=Com\|POS=NOUN`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Tot`, `Case=Gen\|Definite=Def\|Gender=Com\|Number=Sing\|POS=NOUN`, `Case=Acc\|Definite=Def\|POS=PRON\|PronType=Prs`, `Definite=Def\|POS=PRON\|Poss=Yes\|PronType=Prs`, `Case=Nom\|POS=PROPN`, `Case=Nom\|Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Case=Nom\|Definite=Def\|Gender=Com\|Number=Plur\|POS=PRON\|PronType=Prs`, `Definite=Def\|Number=Plur\|POS=DET\|PronType=Prs`, `Case=Gen\|Number=Plur\|POS=ADJ\|Tense=Past\|VerbForm=Part`, `Case=Acc\|Definite=Def\|Gender=Com\|Number=Plur\|POS=PRON\|PronType=Prs`, `Definite=Ind\|Number=Plur\|POS=PRON\|PronType=Rel`, `Mood=Ind\|POS=VERB\|Tense=Past\|VerbForm=Fin`, `Definite=Ind\|Number=Plur\|POS=PRON\|PronType=Int`, `Number=Plur\|POS=DET\|PronType=Ind`, `Case=Gen\|POS=PROPN`, `POS=PROPN`, `Definite=Ind\|Gender=Com\|Number=Sing\|POS=DET\|PronType=Int`, `Definite=Ind\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Tot`, `Gender=Neut\|POS=NOUN`, `Case=Gen\|Definite=Def\|Gender=Com\|Number=Plur\|POS=NOUN`, `Definite=Ind\|Number=Plur\|POS=DET\|PronType=Int`, `Definite=Ind\|Gender=Com\|Number=Sing\|POS=DET\|PronType=Neg`, `POS=VERB\|VerbForm=Sup`, `Case=Gen\|Definite=Def\|Gender=Neut\|Number=Plur\|POS=NOUN`, `Mood=Ind\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Definite=Ind\|Gender=Neut\|NumType=Card\|Number=Sing\|POS=NUM`, `Foreign=Yes\|POS=NOUN`, `Foreign=Yes\|POS=ADJ`, `Definite=Def\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Ind`, `Definite=Ind\|Number=Plur\|POS=DET\|PronType=Ind`, `POS=SYM`, `Case=Nom\|Degree=Pos\|Gender=Neut\|Number=Sing\|POS=ADJ`, `Definite=Def\|Number=Sing\|POS=DET\|PronType=Tot`, `Definite=Ind\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Ind`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Int`, `Case=Nom\|Definite=Ind\|Degree=Sup\|POS=ADJ`, `Definite=Def\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Dem`, `Definite=Ind\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Neg`, `Mood=Sub\|POS=AUX\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Degree=Pos\|Gender=Com\|POS=ADJ`, `Definite=Def\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Definite=Ind\|Gender=Com\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Case=Nom\|Definite=Ind\|Gender=Neut\|Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Part`, `Definite=Def\|Number=Plur\|POS=PRON\|PronType=Ind`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Prs`, `Definite=Ind\|POS=DET\|PronType=Prs`, `Definite=Def\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Prs`, `Definite=Def\|POS=PRON\|Poss=Yes\|PronType=Rel`, `Case=Gen\|Degree=Pos\|Number=Plur\|POS=ADJ`, `Definite=Def\|Number=Plur\|POS=PRON\|Poss=Yes\|PronType=Ind`, `Definite=Def\|Gender=Com\|Number=Sing\|POS=DET\|PronType=Prs`, `Abbr=Yes\|POS=ADJ`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Rel`, `Definite=Ind\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Rel`, `NumType=Card\|POS=NUM`, `POS=INTJ`, `Definite=Ind\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Int`, `Degree=Sup\|POS=ADV\|Polarity=Neg`, `Definite=Ind\|Gender=Com\|Number=Sing\|POS=DET\|PronType=Tot`, `Definite=Ind\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Prs`, `Definite=Def\|POS=PRON\|Poss=Yes\|PronType=Int`, `POS=ADV\|Polarity=Neg`, `Definite=Ind\|Number=Sing\|POS=DET\|PronType=Ind`, `POS=ADJ`, `Case=Nom\|Definite=Ind\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Prs`, `Case=Gen\|Definite=Def\|Degree=Pos\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=NOUN`, `Case=Nom\|Definite=Def\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Tot`, `Gender=Neut\|Number=Sing\|POS=DET\|PronType=Tot`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Neg`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Definite=Ind\|Number=Plur\|POS=DET\|PronType=Neg`, `Case=Nom\|Definite=Def\|Degree=Sup\|Gender=Masc\|Number=Sing\|POS=ADJ`, `Definite=Def\|Gender=Masc\|Number=Sing\|POS=PRON\|PronType=Dem`, `Definite=Def\|Gender=Neut\|Number=Sing\|POS=PRON\|PronType=Tot`, `Definite=Ind\|Gender=Neut\|Number=Sing\|POS=DET\|PronType=Neg`, `Gender=Com\|Number=Sing\|POS=DET\|PronType=Prs`, `Mood=Imp\|POS=VERB\|VerbForm=Fin\|Voice=Pass`, `Case=Nom\|Definite=Def\|Number=Plur\|POS=PRON\|PronType=Ind`, `Case=Acc\|Definite=Def\|POS=PRON\|PronType=Ind`, `Foreign=Yes\|POS=ADP`, `Definite=Ind\|Gender=Com\|Number=Sing\|POS=DET\|PronType=Prs`, `Definite=Def\|POS=PRON\|Poss=Yes\|PronType=Dem`, `Abbr=Yes\|Mood=Imp\|POS=VERB\|VerbForm=Fin\|Voice=Act`, `Mood=Sub\|POS=VERB\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Nom\|Definite=Ind\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Rel`, `Foreign=Yes\|POS=CCONJ`, `POS=DET\|PronType=Art`, `Definite=Ind\|Number=Sing\|POS=DET\|PronType=Prs`, `Definite=Ind\|Number=Plur\|POS=DET\|PronType=Tot`, `Case=Nom\|Definite=Def\|Gender=Com\|Number=Sing\|POS=PRON\|PronType=Ind`, `Case=Nom\|Definite=Def\|Number=Plur\|POS=PRON\|PronType=Rel`, `Case=Acc\|Definite=Def\|Number=Plur\|POS=PRON\|PronType=Tot`, `Definite=Def\|Number=Plur\|POS=PRON\|PronType=Prs`, `Case=Gen\|Definite=Ind\|Degree=Pos\|Gender=Com\|Number=Sing\|POS=ADJ`, `Definite=Def\|Number=Plur\|POS=PRON\|PronType=Tot`, `Degree=Pos\|POS=ADV\|Polarity=Neg`, `Mood=Sub\|POS=VERB\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `POS=PRON\|PronType=Ind`, `Definite=Ind\|POS=DET\|PronType=Neg`, `Definite=Ind\|Number=Plur\|POS=PRON\|PronType=Neg`, `POS=CCONJ\|Polarity=Neg`, `Case=Nom\|Gender=Masc\|Number=Sing\|POS=NOUN`, `Case=Acc\|Gender=Fem\|Number=Sing\|POS=NOUN`, `Case=Nom\|Definite=Def\|Number=Plur\|POS=PRON\|PronType=Tot`, `Definite=Def\|Number=Plur\|POS=DET\|PronType=Tot`, `Mood=Imp\|POS=AUX\|VerbForm=Fin\|Voice=Act`, `Foreign=Yes\|POS=ADV`, `Definite=Def\|POS=PRON\|Poss=Yes\|PronType=Rcp`, `Case=Acc\|Definite=Def\|POS=PRON\|Polarity=Neg\|PronType=Ind` | | **`parser`** | `ROOT`, `acl`, `acl:cleft`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `ccomp`, `compound:prt`, `conj`, `cop`, `csubj`, `dep`, `det`, `dislocated`, `expl`, `fixed`, `flat:name`, `iobj`, `mark`, `nmod`, `nmod:poss`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `obl:agent`, `parataxis`, `punct`, `xcomp` | | **`ner`** | `EVN`, `LOC`, `MSR`, `OBJ`, `ORG`, `PRS`, `TME`, `WRK` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 99.99 | | `TOKEN_P` | 99.95 | | `TOKEN_R` | 99.96 | | `TOKEN_F` | 99.95 | | `TAG_ACC` | 95.14 | | `POS_ACC` | 96.28 | | `MORPH_ACC` | 95.60 | | `MORPH_MICRO_P` | 97.44 | | `MORPH_MICRO_R` | 97.40 | | `MORPH_MICRO_F` | 97.42 | | `SENTS_P` | 91.01 | | `SENTS_R` | 94.44 | | `SENTS_F` | 92.70 | | `DEP_UAS` | 83.24 | | `DEP_LAS` | 78.31 | | `LEMMA_ACC` | 95.51 | | `ENTS_P` | 84.22 | | `ENTS_R` | 75.43 | | `ENTS_F` | 79.58 |
spacy/xx_sent_ud_sm
spacy
2023-10-10T06:35:02Z
906
2
spacy
[ "spacy", "multilingual", "license:cc-by-sa-3.0", "model-index", "region:us" ]
null
2022-03-02T23:29:05Z
--- tags: - spacy language: - multilingual license: cc-by-sa-3.0 model-index: - name: xx_sent_ud_sm results: - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.8588338112 --- ### Details: https://spacy.io/models/xx#xx_sent_ud_sm Multi-language pipeline optimized for CPU. Components: senter. | Feature | Description | | --- | --- | | **Name** | `xx_sent_ud_sm` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `senter` | | **Components** | `senter` | | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | | **Sources** | [Universal Dependencies v2.8 (UD_Afrikaans-AfriBooms, UD_Croatian-SET, UD_Czech-CAC, UD_Czech-CLTT, UD_Danish-DDT, UD_Dutch-Alpino, UD_Dutch-LassySmall, UD_English-EWT, UD_Finnish-FTB, UD_Finnish-TDT, UD_French-GSD, UD_French-Spoken, UD_German-GSD, UD_Indonesian-GSD, UD_Irish-IDT, UD_Italian-TWITTIRO, UD_Korean-GSD, UD_Korean-Kaist, UD_Latvian-LVTB, UD_Lithuanian-ALKSNIS, UD_Lithuanian-HSE, UD_Marathi-UFAL, UD_Norwegian-Bokmaal, UD_Norwegian-Nynorsk, UD_Norwegian-NynorskLIA, UD_Persian-Seraji, UD_Portuguese-Bosque, UD_Portuguese-GSD, UD_Romanian-Nonstandard, UD_Romanian-RRT, UD_Russian-GSD, UD_Russian-Taiga, UD_Serbian-SET, UD_Slovak-SNK, UD_Spanish-GSD, UD_Swedish-Talbanken, UD_Telugu-MTG, UD_Vietnamese-VTB)](https://universaldependencies.org/) (Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell; et al.) | | **License** | `CC BY-SA 3.0` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 98.59 | | `TOKEN_P` | 95.31 | | `TOKEN_R` | 95.72 | | `TOKEN_F` | 95.52 | | `SENTS_P` | 90.66 | | `SENTS_R` | 81.58 | | `SENTS_F` | 85.88 |
spacy/zh_core_web_md
spacy
2023-10-10T06:34:11Z
24
0
spacy
[ "spacy", "token-classification", "zh", "license:mit", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - zh license: mit model-index: - name: zh_core_web_md results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7188227082 - name: NER Recall type: recall value: 0.679010989 - name: NER F Score type: f_score value: 0.6983499096 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.9003849582 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.7049895344 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.652241773 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.7572294372 --- ### Details: https://spacy.io/models/zh#zh_core_web_md Chinese pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler. | Feature | Description | | --- | --- | | **Name** | `zh_core_web_md` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 500000 keys, 20000 unique vectors (300 dimensions) | | **Sources** | [OntoNotes 5](https://catalog.ldc.upenn.edu/LDC2013T19) (Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, Mohammed El-Bachouti, Robert Belvin, Ann Houston)<br />[CoreNLP Universal Dependencies Converter](https://nlp.stanford.edu/software/stanford-dependencies.html) (Stanford NLP Group)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) | | **License** | `MIT` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (100 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `AD`, `AS`, `BA`, `CC`, `CD`, `CS`, `DEC`, `DEG`, `DER`, `DEV`, `DT`, `ETC`, `FW`, `IJ`, `INF`, `JJ`, `LB`, `LC`, `M`, `MSP`, `NN`, `NR`, `NT`, `OD`, `ON`, `P`, `PN`, `PU`, `SB`, `SP`, `URL`, `VA`, `VC`, `VE`, `VV`, `X`, `_SP` | | **`parser`** | `ROOT`, `acl`, `advcl:loc`, `advmod`, `advmod:dvp`, `advmod:loc`, `advmod:rcomp`, `amod`, `amod:ordmod`, `appos`, `aux:asp`, `aux:ba`, `aux:modal`, `aux:prtmod`, `auxpass`, `case`, `cc`, `ccomp`, `compound:nn`, `compound:vc`, `conj`, `cop`, `dep`, `det`, `discourse`, `dobj`, `etc`, `mark`, `mark:clf`, `name`, `neg`, `nmod`, `nmod:assmod`, `nmod:poss`, `nmod:prep`, `nmod:range`, `nmod:tmod`, `nmod:topic`, `nsubj`, `nsubj:xsubj`, `nsubjpass`, `nummod`, `parataxis:prnmod`, `punct`, `xcomp` | | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 95.85 | | `TOKEN_P` | 94.58 | | `TOKEN_R` | 91.36 | | `TOKEN_F` | 92.94 | | `TAG_ACC` | 90.04 | | `SENTS_P` | 78.89 | | `SENTS_R` | 72.80 | | `SENTS_F` | 75.72 | | `DEP_UAS` | 70.50 | | `DEP_LAS` | 65.22 | | `ENTS_P` | 71.88 | | `ENTS_R` | 67.90 | | `ENTS_F` | 69.83 |
spacy/zh_core_web_sm
spacy
2023-10-10T06:34:03Z
174
6
spacy
[ "spacy", "token-classification", "zh", "license:mit", "model-index", "region:us" ]
token-classification
2022-03-02T23:29:05Z
--- tags: - spacy - token-classification language: - zh license: mit model-index: - name: zh_core_web_sm results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.7203462148 - name: NER Recall type: recall value: 0.6493406593 - name: NER F Score type: f_score value: 0.6830029475 - task: name: TAG type: token-classification metrics: - name: TAG (XPOS) Accuracy type: accuracy value: 0.8933253054 - task: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Unlabeled Attachment Score (UAS) type: f_score value: 0.6960047338 - task: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Labeled Attachment Score (LAS) type: f_score value: 0.640776699 - task: name: SENTS type: token-classification metrics: - name: Sentences F-Score type: f_score value: 0.7514211886 --- ### Details: https://spacy.io/models/zh#zh_core_web_sm Chinese pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler. | Feature | Description | | --- | --- | | **Name** | `zh_core_web_sm` | | **Version** | `3.7.0` | | **spaCy** | `>=3.7.0,<3.8.0` | | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `ner` | | **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `ner` | | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | | **Sources** | [OntoNotes 5](https://catalog.ldc.upenn.edu/LDC2013T19) (Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, Mohammed El-Bachouti, Robert Belvin, Ann Houston)<br />[CoreNLP Universal Dependencies Converter](https://nlp.stanford.edu/software/stanford-dependencies.html) (Stanford NLP Group) | | **License** | `MIT` | | **Author** | [Explosion](https://explosion.ai) | ### Label Scheme <details> <summary>View label scheme (100 labels for 3 components)</summary> | Component | Labels | | --- | --- | | **`tagger`** | `AD`, `AS`, `BA`, `CC`, `CD`, `CS`, `DEC`, `DEG`, `DER`, `DEV`, `DT`, `ETC`, `FW`, `IJ`, `INF`, `JJ`, `LB`, `LC`, `M`, `MSP`, `NN`, `NR`, `NT`, `OD`, `ON`, `P`, `PN`, `PU`, `SB`, `SP`, `URL`, `VA`, `VC`, `VE`, `VV`, `X`, `_SP` | | **`parser`** | `ROOT`, `acl`, `advcl:loc`, `advmod`, `advmod:dvp`, `advmod:loc`, `advmod:rcomp`, `amod`, `amod:ordmod`, `appos`, `aux:asp`, `aux:ba`, `aux:modal`, `aux:prtmod`, `auxpass`, `case`, `cc`, `ccomp`, `compound:nn`, `compound:vc`, `conj`, `cop`, `dep`, `det`, `discourse`, `dobj`, `etc`, `mark`, `mark:clf`, `name`, `neg`, `nmod`, `nmod:assmod`, `nmod:poss`, `nmod:prep`, `nmod:range`, `nmod:tmod`, `nmod:topic`, `nsubj`, `nsubj:xsubj`, `nsubjpass`, `nummod`, `parataxis:prnmod`, `punct`, `xcomp` | | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` | </details> ### Accuracy | Type | Score | | --- | --- | | `TOKEN_ACC` | 95.85 | | `TOKEN_P` | 94.58 | | `TOKEN_R` | 91.36 | | `TOKEN_F` | 92.94 | | `TAG_ACC` | 89.33 | | `SENTS_P` | 77.85 | | `SENTS_R` | 72.62 | | `SENTS_F` | 75.14 | | `DEP_UAS` | 69.60 | | `DEP_LAS` | 64.08 | | `ENTS_P` | 72.03 | | `ENTS_R` | 64.93 | | `ENTS_F` | 68.30 |