BelSmile: a biomedical semantic role labeling approach for extracting biological expression language from text

Po-Ting Lai, Yu-Yan Lo, Ming-Siang Huang, Yu-Cheng Hsiao, Richard Tzong-Han Tsai
2016 Database: The Journal of Biological Databases and Curation  
Citation details: Lai,P.-T, Lo, Y.-Y., Huang,M.-S. et al. BelSmile: a biomedical semantic role labeling approach for extracting biological expression language from text. Abstract Biological expression language (BEL) is one of the most popular languages to represent the causal and correlative relationships among biological events. Automatically extracting and representing biomedical events using BEL can help biologists quickly survey and understand relevant literature. Recently, many researchers
more » ... have shown interest in biomedical event extraction. However, the task is still a challenge for current systems because of the complexity of integrating different information extraction tasks such as named entity recognition (NER), named entity normalization (NEN) and relation extraction into a single system. In this study, we introduce our BelSmile system, which uses a semantic-role-labeling (SRL)-based approach to extract the NEs and events for BEL statements. BelSmile combines our previous NER, NEN and SRL systems. We evaluate BelSmile using the BioCreative V BEL task dataset. Our system achieved an F-score of 27.8%, 7% higher than the top BioCreative V system. The three main contributions of this study are (i) an effective pipeline approach to extract BEL statements, and (ii) a syntactic-based labeler to extract subject-verb-object tuples. We also implement a web-based version of BelSmile (iii) that is publicly available at iisrserv.csie.ncu.edu.tw/belsmile.
doi:10.1093/database/baw064 pmid:27173520 pmcid:PMC4865328 fatcat:wx42b3ivafau3djwpxcbkeuhyi