metadata

language:
  - en
bigbio_language:
  - English
license: cc-by-4.0
multilinguality: monolingual
bigbio_license_shortname: CC_BY_4p0
pretty_name: TwADR-L
homepage: https://zenodo.org/record/55013
bigbio_pubmed: false
bigbio_public: true
bigbio_tasks:
  - NAMED_ENTITY_RECOGNITION
  - NAMED_ENTITY_DISAMBIGUATION

Dataset Card for TwADR-L

Dataset Description

Homepage: https://zenodo.org/record/55013
Pubmed: False
Public: True
Tasks: NER,NED

The TwADR-L dataset contains medical concepts written on social media (Twitter) mapped to how they are formally written in medical ontologies (SIDER 4).

Citation Information


@inproceedings{limsopatham-collier-2016-normalising,
    title = "Normalising Medical Concepts in Social Media Texts by Learning Semantic Representation",
    author = "Limsopatham, Nut  and
      Collier, Nigel",
    booktitle = "Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = aug,
    year = "2016",
    address = "Berlin, Germany",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/P16-1096",
    doi = "10.18653/v1/P16-1096",
    pages = "1014--1023",
}