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---
language:
- en
bigbio_language:
- English
license: cc0-1.0
multilinguality: monolingual
bigbio_license_shortname: CC0_1p0
pretty_name: NLM-Chem
homepage: https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-2
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- NAMED_ENTITY_RECOGNITION
- NAMED_ENTITY_DISAMBIGUATION
- 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:** Named Entity Recognition, Named Entity Disambiguation, Text Classification
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}
}
```
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