---

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"
}