| |
|
| | --- |
| | 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:** 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} |
| | } |
| | |
| | ``` |
| |
|
