BioRelEx 1.0: Biological Relation Extraction Benchmark

Hrant Khachatrian, Lilit Nersisyan, Karen Hambardzumyan, Tigran Galstyan, Anna Hakobyan, Arsen Arakelyan, Andrey Rzhetsky, Aram Galstyan


Abstract
Automatic extraction of relations and interactions between biological entities from scientific literature remains an extremely challenging problem in biomedical information extraction and natural language processing in general. One of the reasons for slow progress is the relative scarcity of standardized and publicly available benchmarks. In this paper we introduce BioRelEx, a new dataset of fully annotated sentences from biomedical literature that capture binding interactions between proteins and/or biomolecules. To foster reproducible research on the interaction extraction task, we define a precise and transparent evaluation process, tools for error analysis and significance tests. Finally, we conduct extensive experiments to evaluate several baselines, including SciIE, a recently introduced neural multi-task architecture that has demonstrated state-of-the-art performance on several tasks.
Anthology ID:
W19-5019
Volume:
Proceedings of the 18th BioNLP Workshop and Shared Task
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Dina Demner-Fushman, Kevin Bretonnel Cohen, Sophia Ananiadou, Junichi Tsujii
Venue:
BioNLP
SIG:
SIGBIOMED
Publisher:
Association for Computational Linguistics
Note:
Pages:
176–190
Language:
URL:
https://aclanthology.org/W19-5019
DOI:
10.18653/v1/W19-5019
Bibkey:
Cite (ACL):
Hrant Khachatrian, Lilit Nersisyan, Karen Hambardzumyan, Tigran Galstyan, Anna Hakobyan, Arsen Arakelyan, Andrey Rzhetsky, and Aram Galstyan. 2019. BioRelEx 1.0: Biological Relation Extraction Benchmark. In Proceedings of the 18th BioNLP Workshop and Shared Task, pages 176–190, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
BioRelEx 1.0: Biological Relation Extraction Benchmark (Khachatrian et al., BioNLP 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-5019.pdf
Code
 YerevaNN/BioRelEx
Data
SciERC