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---
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",
}
```
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