metadata

language:
  - en
bigbio_language:
  - English
license: other
multilinguality: monolingual
bigbio_license_shortname: GENIA_PROJECT_LICENSE
pretty_name: BioNLP 2011 REL
homepage: https://github.com/openbiocorpora/bionlp-st-2011-rel
bigbio_pubmed: true
bigbio_public: true
bigbio_tasks:
  - NAMED_ENTITY_RECOGNITION
  - RELATION_EXTRACTION
  - COREFERENCE_RESOLUTION

Dataset Card for BioNLP 2011 REL

Dataset Description

Homepage: https://github.com/openbiocorpora/bionlp-st-2011-rel
Pubmed: True
Public: True
Tasks: NER,RE,COREF

The Entity Relations (REL) task is a supporting task of the BioNLP Shared Task 2011. The task concerns the extraction of two types of part-of relations between a gene/protein and an associated entity.

Citation Information

@inproceedings{10.5555/2107691.2107703,
author = {Pyysalo, Sampo and Ohta, Tomoko and Tsujii, Jun'ichi},
title = {Overview of the Entity Relations (REL) Supporting Task of BioNLP Shared Task 2011},
year = {2011},
isbn = {9781937284091},
publisher = {Association for Computational Linguistics},
address = {USA},
abstract = {This paper presents the Entity Relations (REL) task,
a supporting task of the BioNLP Shared Task 2011. The task concerns
the extraction of two types of part-of relations between a gene/protein
and an associated entity. Four teams submitted final results for
the REL task, with the highest-performing system achieving 57.7%
F-score. While experiments suggest use of the data can help improve
event extraction performance, the task data has so far received only
limited use in support of event extraction. The REL task continues
as an open challenge, with all resources available from the shared
task website.},
booktitle = {Proceedings of the BioNLP Shared Task 2011 Workshop},
pages = {83–88},
numpages = {6},
location = {Portland, Oregon},
series = {BioNLP Shared Task '11}
}