| 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", | |
| } | |
| ``` | |