From POS tagging to dependency parsing for biomedical event extraction
Quoc Nguyen Dat, Karin Verspoor
BMC BIOINFORMATICS | BMC | Published : 2019
BACKGROUND: Given the importance of relation or event extraction from biomedical research publications to support knowledge capture and synthesis, and the strong dependency of approaches to this information extraction task on syntactic information, it is valuable to understand which approaches to syntactic processing of biomedical text have the highest performance. RESULTS: We perform an empirical study comparing state-of-the-art traditional feature-based and neural network-based models for two core natural language processing tasks of part-of-speech (POS) tagging and dependency parsing on two benchmark biomedical corpora, GENIA and CRAFT. To the best of our knowledge, there is no recent wor..View full abstract
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Awarded by ARC Discovery Project
Awarded by ARC Linkage Project
This work was supported by the ARC Discovery Project DP150101550 and ARC Linkage Project LP160101469.