| # XCOPA | |
| ### Paper | |
| Title: `XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning` | |
| Abstract: https://ducdauge.github.io/files/xcopa.pdf | |
| The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across languages. | |
| The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around the globe. | |
| The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. | |
| All the details about the creation of XCOPA and the implementation of the baselines are available in the paper. | |
| Homepage: https://github.com/cambridgeltl/xcopa | |
| ### Citation | |
| ``` | |
| @inproceedings{ponti2020xcopa, | |
| title={{XCOPA: A} Multilingual Dataset for Causal Commonsense Reasoning}, | |
| author={Edoardo M. Ponti, Goran Glava\v{s}, Olga Majewska, Qianchu Liu, Ivan Vuli\'{c} and Anna Korhonen}, | |
| booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)}, | |
| year={2020}, | |
| url={https://ducdauge.github.io/files/xcopa.pdf} | |
| } | |
| ``` | |
| ### Groups and Tasks | |
| #### Groups | |
| * `xcopa` | |
| #### Tasks | |
| * `xcopa_et`: Estonian | |
| * `xcopa_ht`: Haitian Creole | |
| * `xcopa_id`: Indonesian | |
| * `xcopa_it`: Italian | |
| * `xcopa_qu`: Cusco-Collao Quechua | |
| * `xcopa_sw`: Kiswahili | |
| * `xcopa_ta`: Tamil | |
| * `xcopa_th`: Thai | |
| * `xcopa_tr`: Turkish | |
| * `xcopa_vi`: Vietnamese | |
| * `xcopa_zh`: Mandarin Chinese | |
| ### Checklist | |
| For adding novel benchmarks/datasets to the library: | |
| * [ ] Is the task an existing benchmark in the literature? | |
| * [ ] Have you referenced the original paper that introduced the task? | |
| * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? | |
| If other tasks on this dataset are already supported: | |
| * [ ] Is the "Main" variant of this task clearly denoted? | |
| * [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? | |
| * [ ] Have you noted which, if any, published evaluation setups are matched by this variant? | |