Dataset Open Access

NLMChem a new resource for chemical entity recognition in PubMed full-text literature

Islamaj, Rezarta; Leaman, Robert; Lu, Zhiyong


BibTeX Export

@dataset{islamaj_rezarta_2021_4628233,
  author       = {Islamaj, Rezarta and
                  Leaman, Robert and
                  Lu, Zhiyong},
  title        = {{NLMChem a new resource for chemical entity 
                   recognition in PubMed full-text literature}},
  month        = mar,
  year         = 2021,
  note         = {{<p>We include the document of annotation 
                   guidelines, which makes it clear that the corpus
                   can be combined with ChemDNER and BC5CDR corpora,
                   which contain chemical name annotations, and name
                   and MeSH annotations for chemicals respectively to
                   further improve Chemical NER in biomedical
                   literature. </p>  <p>The corpus has been divided
                   into train/dev/test to facilitate benchmarking and
                   comparisons. </p>  <p>The data annotations are
                   inline in the BioC XML format, which is a
                   minimalistic approach to facilitate text mining.
                   We also maintain a copy here: <a href="https://www
                   .ncbi.nlm.nih.gov/research/bionlp/">https://www.nc
                   bi.nlm.nih.gov/research/bionlp/</a></p> <p>Funding
                   provided by: U.S. National Library of
                   Medicine<br>Crossref Funder Registry ID:
                   http://dx.doi.org/10.13039/100000092<br>Award
                   Number: Intramural Research Program</p>}},
  publisher    = {Zenodo},
  doi          = {10.5061/dryad.3tx95x6dz},
  url          = {https://doi.org/10.5061/dryad.3tx95x6dz}
}