bigbio/nlmchem
NLM-Chem corpus consists of 150 full-text articles from the PubMed Central Open Access dataset, comprising 67 different chemical journals, aiming to cover a general distribution of usage of chemical names in the biomedical literature. Articles were selected so that human annotation was most valuable (meaning that they were rich in bio-entities, and current state-of-the-art named entity recognition systems disagreed on bio-entity recognition.
language:
- en bigbio_language:
- English license: cc0-1.0 multilinguality: monolingual bigbiolicenseshortname: CC01p0 prettyname: NLM-Chem homepage: https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-2 bigbiopubmed: True bigbiopublic: True bigbio_tasks:
- NAMEDENTITYRECOGNITION
- NAMEDENTITYDISAMBIGUATION
- TEXT_CLASSIFICATION ---
Dataset Card for NLM-Chem
Dataset Description
- Homepage: https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-2
- Pubmed: True
- Public: True
- Tasks: NER,NED,TXTCLASS
NLM-Chem corpus consists of 150 full-text articles from the PubMed Central Open Access dataset, comprising 67 different chemical journals, aiming to cover a general distribution of usage of chemical names in the biomedical literature. Articles were selected so that human annotation was most valuable (meaning that they were rich in bio-entities, and current state-of-the-art named entity recognition systems disagreed on bio-entity recognition.
Citation Information
@Article{islamaj2021nlm,
title={NLM-Chem, a new resource for chemical entity recognition in PubMed full text literature},
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},
journal={Scientific Data},
volume={8},
number={1},
pages={1--12},
year={2021},
publisher={Nature Publishing Group}
}