Chinese pronominal anaphora resolution using lexical knowledge and entropy-based weight

Authors:
Dian-Song Wu;Tyne Liang
Affiliations:
Department of Computer Science, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu, Taiwan;Department of Computer Science, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu, Taiwan
Venue:
Journal of the American Society for Information Science and Technology
Year:
2008

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Abstract

Pronominal anaphors are commonly observed in written texts. Inthis article, effective Chinese pronominal anaphora resolution isaddressed by using lexical knowledge acquisition and saliencemeasurement. The lexical knowledge acquisition is aimed to extractmore semantic features, such as gender, number, and collocatecompatibility by employing multiple resources. The presentedsalience measurement is based on entropy-based weighting onselecting antecedent candidates. The resolution is justified with areal corpus and compared with a rule-based model. Experimentalresults by five-fold cross-validation show that our approach yields82.5% success rate on 1343 anaphoric instances. In comparison witha general rule-based approach, the performance is improved by 7%.© 2008 Wiley Periodicals, Inc.