File size: 1,677 Bytes
fbd0581 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
---
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:** NER,NED,RE
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}
}
```
|