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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: other |
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multilinguality: monolingual |
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bigbio_license_shortname: GENIA_PROJECT_LICENSE |
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pretty_name: BioNLP 2011 REL |
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homepage: https://github.com/openbiocorpora/bionlp-st-2011-rel |
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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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- RELATION_EXTRACTION |
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- COREFERENCE_RESOLUTION |
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--- |
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# Dataset Card for BioNLP 2011 REL |
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## Dataset Description |
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- **Homepage:** https://github.com/openbiocorpora/bionlp-st-2011-rel |
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- **Pubmed:** True |
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- **Public:** True |
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- **Tasks:** NER,RE,COREF |
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The Entity Relations (REL) task is a supporting task of the BioNLP Shared Task 2011. |
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The task concerns the extraction of two types of part-of relations between a |
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gene/protein and an associated entity. |
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## Citation Information |
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``` |
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@inproceedings{10.5555/2107691.2107703, |
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author = {Pyysalo, Sampo and Ohta, Tomoko and Tsujii, Jun'ichi}, |
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title = {Overview of the Entity Relations (REL) Supporting Task of BioNLP Shared Task 2011}, |
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year = {2011}, |
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isbn = {9781937284091}, |
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publisher = {Association for Computational Linguistics}, |
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address = {USA}, |
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abstract = {This paper presents the Entity Relations (REL) task, |
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a supporting task of the BioNLP Shared Task 2011. The task concerns |
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the extraction of two types of part-of relations between a gene/protein |
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and an associated entity. Four teams submitted final results for |
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the REL task, with the highest-performing system achieving 57.7% |
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F-score. While experiments suggest use of the data can help improve |
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event extraction performance, the task data has so far received only |
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limited use in support of event extraction. The REL task continues |
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as an open challenge, with all resources available from the shared |
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task website.}, |
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booktitle = {Proceedings of the BioNLP Shared Task 2011 Workshop}, |
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pages = {83–88}, |
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numpages = {6}, |
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location = {Portland, Oregon}, |
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series = {BioNLP Shared Task '11} |
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} |
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``` |
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