Automatic classification of verbs in biomedical texts

Authors:
Anna Korhonen;Yuval Krymolowski;Nigel Collier
Affiliations:
University of Cambridge, Cambridge, UK;Technion, Haifa, Israel;National Institute of Informatics, Tokyo, Japan
Venue:
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Year:
2006

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Abstract

Lexical classes, when tailored to the application and domain in question, can provide an effective means to deal with a number of natural language processing (NLP) tasks. While manual construction of such classes is difficult, recent research shows that it is possible to automatically induce verb classes from cross-domain corpora with promising accuracy. We report a novel experiment where similar technology is applied to the important, challenging domain of biomedicine. We show that the resulting classification, acquired from a corpus of biomedical journal articles, is highly accurate and strongly domain-specific. It can be used to aid BIO-NLP directly or as useful material for investigating the syntax and semantics of verbs in biomedical texts.