metadata

language:
  - en
bigbio_language:
  - English
license: cc-by-sa-4.0
multilinguality: monolingual
bigbio_license_shortname: CC_BY_SA_4p0
pretty_name: BEAR
homepage: https://www.ims.uni-stuttgart.de/en/research/resources/corpora/bioclaim/
bigbio_pubmed: false
bigbio_public: true
bigbio_tasks:
  - NAMED_ENTITY_RECOGNITION
  - RELATION_EXTRACTION

Dataset Card for BEAR

Dataset Description

Homepage: https://www.ims.uni-stuttgart.de/en/research/resources/corpora/bioclaim/
Pubmed: False
Public: True
Tasks: NER, RE

A dataset of 2100 Twitter posts annotated with 14 different types of biomedical entities (e.g., disease, treatment, risk factor, etc.) and 20 relation types (including caused, treated, worsens, etc.).

Citation Information

@InProceedings{wuehrl_klinger_2022,
  author    = {Wuehrl, Amelie  and  Klinger, Roman},
  title     = {Recovering Patient Journeys: A Corpus of Biomedical Entities and Relations on  Twitter (BEAR)},
  booktitle      = {Proceedings of The 13th Language Resources and Evaluation Conference},
  month          = {June},
  year           = {2022},
  address        = {Marseille, France},
  publisher      = {European Language Resources Association}
}