BioCreative V CDR task corpus: a resource for chemical disease relation extraction

Community-run, formal evaluations and manually annotated text corpora are critically important for advancing biomedical text-mining research. Recently in BioCreative V, a new challenge was organized for the tasks of disease named entity recognition (DNER) and chemical-induced disease (CID) relation extraction. Given the nature of both tasks, a test collection is required to contain both disease/chemical annotations and relation annotations in the same set of articles. Despite previous efforts in biomedical corpus construction, none was found to be sufficient for the task. Thus, we developed our own corpus called BC5CDR during the challenge by inviting a team of Medical Subject Headings (MeSH) indexers for…

• CK
  China Knowledge Centre for Engineering Sciences and Technology
• NI
  National Institutes of Health
• FR
  Fundamental Research Funds for the Central Universities
• NI
  National Institute of Environmental Health Sciences

  Awards: ES019604, ES014065