A comparative study of syntactic parsers for event extraction

Authors:
Makoto Miwa;Sampo Pyysalo;Tadayoshi Hara;Jun'ichi Tsujii
Affiliations:
The University of Tokyo, Bunkyo-ku, Tokyo, Japan;The University of Tokyo, Bunkyo-ku, Tokyo, Japan;The University of Tokyo, Bunkyo-ku, Tokyo, Japan;The University of Tokyo, Bunkyo-ku, Tokyo, Japan and University of Manchester, UK and National Center for Text Mining, UK
Venue:
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Year:
2010

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Abstract

The extraction of biomolecular events from text is an important task for a number of domain applications such as pathway construction. Several syntactic parsers have been used in Biomedical Natural Language Processing (BioNLP) applications, and the BioNLP 2009 Shared Task results suggest that incorporation of syntactic analysis is important to achieving state-of-the-art performance. Direct comparison of parsers is complicated by to differences in the such as the division between phrase structure- and dependency-based analyses and the variety of output formats, structures and representations applied. In this paper, we present a task-oriented comparison of five parsers, measuring their contribution to biomolecular event extraction using a state-of-the-art event extraction system. The results show that the parsers with domain models using dependency formats provide very similar performance, and that an ensemble of different parsers in different formats can improve the event extraction system.