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--- |
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language: |
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- en |
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bigbio_language: |
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- English |
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license: unknown |
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multilinguality: monolingual |
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bigbio_license_shortname: UNKNOWN |
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pretty_name: PICO Annotation |
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homepage: https://github.com/Markus-Zlabinger/pico-annotation |
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bigbio_pubmed: True |
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bigbio_public: True |
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bigbio_tasks: |
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- NAMED_ENTITY_RECOGNITION |
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--- |
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# Dataset Card for PICO Annotation |
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## Dataset Description |
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- **Homepage:** https://github.com/Markus-Zlabinger/pico-annotation |
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- **Pubmed:** True |
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- **Public:** True |
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- **Tasks:** NER |
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This dataset contains annotations for Participants, Interventions, and Outcomes (referred to as PICO task). |
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For 423 sentences, annotations collected by 3 medical experts are available. |
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To get the final annotations, we perform the majority voting. |
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## Citation Information |
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``` |
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@inproceedings{zlabinger-etal-2020-effective, |
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title = "Effective Crowd-Annotation of Participants, Interventions, and Outcomes in the Text of Clinical Trial Reports", |
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author = {Zlabinger, Markus and |
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Sabou, Marta and |
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Hofst{"a}tter, Sebastian and |
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Hanbury, Allan}, |
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booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020", |
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month = nov, |
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year = "2020", |
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address = "Online", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2020.findings-emnlp.274", |
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doi = "10.18653/v1/2020.findings-emnlp.274", |
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pages = "3064--3074", |
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} |
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``` |
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