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app.py
CHANGED
@@ -19,7 +19,7 @@ relation_extractor = CustomGLiNERRelationExtractor(model=model, return_index=Tru
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# Sample text
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SAMPLE_TEXT = (
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"Encuesta Nacional de Hogares (ENAHO) is the Peruvian version of the Living Standards Measurement Survey, e.g. a nationally representative household survey collected monthly on a continuous basis. For our analysis, we use data from January 2007 to December 2020. The survey covers a wide variety of topics, including basic demographics, educational background, labor market conditions, crime victimization, and a module on respondent’s perceptions about the main problems in the country and trust in different local and national‐level institutions.
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)
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# Post-processing: prune acronyms and self-relations
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@@ -177,7 +177,7 @@ with gr.Blocks() as demo:
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4. Click **Get Model Predictions** to view the raw JSON output.
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**Resources**
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- **Model:** [
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- **Paper:** _Large Language Models and Synthetic Data for Monitoring Dataset Mentions in Research Papers_ – ArXiv: [2502.10263](https://arxiv.org/pdf/2502.10263)
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- [GLiNER GitHub Repo](https://github.com/urchade/GLiNER)
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- [Project Docs](https://worldbank.github.io/ai4data-use/docs/introduction.html)
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# Sample text
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SAMPLE_TEXT = (
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"Encuesta Nacional de Hogares (ENAHO) is the Peruvian version of the Living Standards Measurement Survey, e.g. a nationally representative household survey collected monthly on a continuous basis. For our analysis, we use data from January 2007 to December 2020. The survey covers a wide variety of topics, including basic demographics, educational background, labor market conditions, crime victimization, and a module on respondent’s perceptions about the main problems in the country and trust in different local and national‐level institutions."
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)
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# Post-processing: prune acronyms and self-relations
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4. Click **Get Model Predictions** to view the raw JSON output.
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**Resources**
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- **Model:** [{DATA_MODEL_ID}](https://huggingface.co/{DATA_MODEL_ID})
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- **Paper:** _Large Language Models and Synthetic Data for Monitoring Dataset Mentions in Research Papers_ – ArXiv: [2502.10263](https://arxiv.org/pdf/2502.10263)
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- [GLiNER GitHub Repo](https://github.com/urchade/GLiNER)
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- [Project Docs](https://worldbank.github.io/ai4data-use/docs/introduction.html)
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