multilinguality:monolingual language:en license:unknown region:us
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).
@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}
}

---
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}
}

```
