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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: cc0-1.0 |
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multilinguality: monolingual |
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bigbio_license_shortname: CC0_1p0 |
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pretty_name: NLM-Chem |
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homepage: https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-2 |
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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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- NAMED_ENTITY_DISAMBIGUATION |
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- TEXT_CLASSIFICATION |
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--- |
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# Dataset Card for NLM-Chem |
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## Dataset Description |
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- **Homepage:** https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-2 |
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- **Pubmed:** True |
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- **Public:** True |
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- **Tasks:** NER,NED,TXTCLASS |
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NLM-Chem corpus consists of 150 full-text articles from the PubMed Central Open Access dataset, |
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comprising 67 different chemical journals, aiming to cover a general distribution of usage of chemical |
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names in the biomedical literature. |
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Articles were selected so that human annotation was most valuable (meaning that they were rich in bio-entities, |
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and current state-of-the-art named entity recognition systems disagreed on bio-entity recognition. |
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## Citation Information |
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``` |
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@Article{islamaj2021nlm, |
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title={NLM-Chem, a new resource for chemical entity recognition in PubMed full text literature}, |
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author={Islamaj, Rezarta and Leaman, Robert and Kim, Sun and Kwon, Dongseop and Wei, Chih-Hsuan and Comeau, Donald C and Peng, Yifan and Cissel, David and Coss, Cathleen and Fisher, Carol and others}, |
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journal={Scientific Data}, |
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volume={8}, |
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number={1}, |
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pages={1--12}, |
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year={2021}, |
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publisher={Nature Publishing Group} |
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} |
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``` |
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