Datasets:

Languages:
English
License:
bc5cdr / README.md
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---
language:
- en
bigbio_language:
- English
license: other
multilinguality: monolingual
bigbio_license_shortname: PUBLIC_DOMAIN_MARK_1p0
pretty_name: BC5CDR
homepage: http://www.biocreative.org/tasks/biocreative-v/track-3-cdr/
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- NAMED_ENTITY_RECOGNITION
- NAMED_ENTITY_DISAMBIGUATION
- RELATION_EXTRACTION
---
# Dataset Card for BC5CDR
## Dataset Description
- **Homepage:** http://www.biocreative.org/tasks/biocreative-v/track-3-cdr/
- **Pubmed:** True
- **Public:** True
- **Tasks:** Named Entity Recognition, Named Entity Disambiguation, Relation Extraction
The BioCreative V Chemical Disease Relation (CDR) dataset is a large annotated text corpus of human annotations of all chemicals, diseases and their interactions in 1,500 PubMed articles.
## Citation Information
```
@article{DBLP:journals/biodb/LiSJSWLDMWL16,
author = {Jiao Li and
Yueping Sun and
Robin J. Johnson and
Daniela Sciaky and
Chih{-}Hsuan Wei and
Robert Leaman and
Allan Peter Davis and
Carolyn J. Mattingly and
Thomas C. Wiegers and
Zhiyong Lu},
title = {BioCreative {V} {CDR} task corpus: a resource for chemical disease
relation extraction},
journal = {Database J. Biol. Databases Curation},
volume = {2016},
year = {2016},
url = {https://doi.org/10.1093/database/baw068},
doi = {10.1093/database/baw068},
timestamp = {Thu, 13 Aug 2020 12:41:41 +0200},
biburl = {https://dblp.org/rec/journals/biodb/LiSJSWLDMWL16.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
```