Word sense disambiguation for event trigger word detection in biomedicine

被引:0
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作者
David Martinez
Timothy Baldwin
机构
[1] The University of Melbourne,NICTA VRL
[2] The University of Melbourne,Department of Computer Science and Software Engineering
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Target Word; Word Type; Ambiguous Word; Vector Space Model; Name Entity Recognition;
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摘要
This paper describes a method for detecting event trigger words in biomedical text based on a word sense disambiguation (WSD) approach. We first investigate the applicability of existing WSD techniques to trigger word disambiguation in the BioNLP 2009 shared task data, and find that we are able to outperform a traditional CRF-based approach for certain word types. On the basis of this finding, we combine the WSD approach with the CRF, and obtain significant improvements over the standalone CRF, gaining particularly in recall.
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