language: | |
- en | |
bigbio_language: | |
- English | |
license: unknown | |
multilinguality: monolingual | |
bigbio_license_shortname: UNKNOWN | |
pretty_name: Bio-SimLex | |
homepage: https://github.com/cambridgeltl/bio-simverb | |
bigbio_pubmed: True | |
bigbio_public: True | |
bigbio_tasks: | |
- SEMANTIC_SIMILARITY | |
# Dataset Card for Bio-SimLex | |
## Dataset Description | |
- **Homepage:** https://github.com/cambridgeltl/bio-simverb | |
- **Pubmed:** True | |
- **Public:** True | |
- **Tasks:** STS | |
Bio-SimLex enables intrinsic evaluation of word representations. This evaluation can serve as a predictor of performance on various downstream tasks in the biomedical domain. The results on Bio-SimLex using standard word representation models highlight the importance of developing dedicated evaluation resources for NLP in biomedicine for particular word classes (e.g. verbs). | |
## Citation Information | |
``` | |
@article{article, | |
title = { | |
Bio-SimVerb and Bio-SimLex: Wide-coverage evaluation sets of word | |
similarity in biomedicine | |
}, | |
author = {Chiu, Billy and Pyysalo, Sampo and Vulić, Ivan and Korhonen, Anna}, | |
year = 2018, | |
month = {02}, | |
journal = {BMC Bioinformatics}, | |
volume = 19, | |
pages = {}, | |
doi = {10.1186/s12859-018-2039-z} | |
} | |
``` | |