| 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} | |
| } | |
| ``` | |