Improving semantic role labeling with word sense

Authors:
Wanxiang Che;Ting Liu;Yongqiang Li
Affiliations:
Harbin Institute of Technology, China;Harbin Institute of Technology, China;Harbin Institute of Technology, China
Venue:
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Year:
2010

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Abstract

Semantic role labeling (SRL) not only needs lexical and syntactic information, but also needs word sense information. However, because of the lack of corpus annotated with both word senses and semantic roles, there is few research on using word sense for SRL. The release of OntoNotes provides an opportunity for us to study how to use word sense for SRL. In this paper, we present some novel word sense features for SRL and find that they can improve the performance significantly.