Biomedical events extraction using the hidden vector state model

摘要

ObjectiveBiomedical events extraction concerns about events describing changes on the state of bio-molecules from literature. Comparing to the protein–protein interactions (PPIs) extraction task which often only involves the extraction of binary relations between two proteins, biomedical events extraction is much harder since it needs to deal with complex events consisting of embedded or hierarchical relations among proteins, events, and their textual triggers. In this paper, we propose an information extraction system based on the hidden vector state (HVS) model, called HVS-BioEvent, for biomedical events extraction, and investigate its capability in extracting complex events.