title: Coreference resolution improves extraction of Biological Expression Language statements from texts.
abstract: We describe a system that automatically extracts biological events from biomedical journal articles, and translates those events into Biological Expression Language (BEL) statements. The system incorporates existing text mining components for coreference resolution, biological event extraction and a previously formally untested strategy for BEL statement generation. Although addressing the BEL track (Track 4) at BioCreative V (2015), we also investigate how incorporating coreference resolution might impact event extraction in the biomedical domain. In this paper, we report that our system achieved the best performance of 20.2 and 35.2 in F-score for the full BEL statement level on both stage 1, and stage 2 using provided gold standard entities, respectively. We also report that our results evaluated on the training dataset show benefit from integrating coreference resolution with event extraction.
authors.affiliation: Department of Computing and Information Systems, the University of Melbourne National ICT Australia (NICTA) Victoria Research Laboratory, Parkville, Victoria, Australia.
authors.forename: Miji
authors.initials: M
authors.lastname: Choi
authors.affiliation: NCBI, Bethesda, MD, USA.
authors.forename: Haibin
authors.initials: H
authors.lastname: Liu
authors.affiliation: University of Colorado School of Medicine, Aurora, CO, USA.
authors.forename: William
authors.initials: W
authors.lastname: Baumgartner
authors.affiliation: Department of Computing and Information Systems, the University of Melbourne.
authors.forename: Justin
authors.initials: J
authors.lastname: Zobel
authors.affiliation: Department of Computing and Information Systems, the University of Melbourne karin.verspoor@unimelb.edu.au.
authors.forename: Karin
authors.initials: K
authors.lastname: Verspoor
mesh_terms: D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D011381:Programming Languages