language:
- en
bigbio_language:
- English
license: unknown
multilinguality: monolingual
bigbio_license_shortname: UNKNOWN
pretty_name: BioRelEx
homepage: https://github.com/YerevaNN/BioRelEx
bigbio_pubmed: true
bigbio_public: true
bigbio_tasks:
- NAMED_ENTITY_RECOGNITION
- NAMED_ENTITY_DISAMBIGUATION
- RELATION_EXTRACTION
- COREFERENCE_RESOLUTION
Dataset Card for BioRelEx
Dataset Description
- Homepage: https://github.com/YerevaNN/BioRelEx
- Pubmed: True
- Public: True
- Tasks: NER,NED,RE,COREF
BioRelEx is a biological relation extraction dataset. Version 1.0 contains 2010 annotated sentences that describe binding interactions between various biological entities (proteins, chemicals, etc.). 1405 sentences are for training, another 201 sentences are for validation. They are publicly available at https://github.com/YerevaNN/BioRelEx/releases. Another 404 sentences are for testing which are kept private for at this Codalab competition https://competitions.codalab.org/competitions/20468. All sentences contain words "bind", "bound" or "binding". For every sentence we provide: 1) Complete annotations of all biological entities that appear in the sentence 2) Entity types (32 types) and grounding information for most of the proteins and families (links to uniprot, interpro and other databases) 3) Coreference between entities in the same sentence (e.g. abbreviations and synonyms) 4) Binding interactions between the annotated entities 5) Binding interaction types: positive, negative (A does not bind B) and neutral (A may bind to B)
Citation Information
@inproceedings{khachatrian2019biorelex,
title = "{B}io{R}el{E}x 1.0: Biological Relation Extraction Benchmark",
author = "Khachatrian, Hrant and
Nersisyan, Lilit and
Hambardzumyan, Karen and
Galstyan, Tigran and
Hakobyan, Anna and
Arakelyan, Arsen and
Rzhetsky, Andrey and
Galstyan, Aram",
booktitle = "Proceedings of the 18th BioNLP Workshop and Shared Task",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-5019",
doi = "10.18653/v1/W19-5019",
pages = "176--190"
}