標題: Chinese Pronominal Anaphora Resolution Using Lexical Knowledge and Entropy-Based Weight
作者: Wu, Dian-Song
Liang, Tyne
資訊工程學系
Department of Computer Science
公開日期: 1-十一月-2008
摘要: Pronominal anaphors are commonly observed in written texts. In this article, effective Chinese pronominal anaphora resolution is addressed by using lexical knowledge acquisition and salience measurement. The lexical knowledge acquisition is aimed to extract more semantic features, such as gender, number, and collocate compatibility by employing multiple resources. The presented salience measurement is based on entropy-based weighting on selecting antecedent candidates. The resolution is justified with a real corpus and compared with a rule-based model. Experimental results by five-fold cross-validation show that our approach yields 82.5% success rate on 1343 anaphoric instances. In comparison with a general rule-based approach, the performance is improved by 7%.
URI: http://dx.doi.org/10.1002/asi.20922
http://hdl.handle.net/11536/15552
ISSN: 1532-2882
DOI: 10.1002/asi.20922
期刊: JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY
Volume: 59
Issue: 13
起始頁: 2138
結束頁: 2145
顯示於類別:期刊論文


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  1. 000260484000010.pdf