標題: Improving Chinese pronominal anaphora resolution by extensive feature representation and confidence estimation
作者: Liang, Tyne
Wu, Dian-Song
資訊工程學系
Department of Computer Science
關鍵字: pronominal anaphora resolution;maximum entropy model;Chinese;discourse
公開日期: 2008
摘要: Pronominal anaphora resolution denotes antecedent identification for anaphoric pronouns expressed in discourses. Effective resolution relies on the kinds of features to be concerned and how they are appropriately weighted at antecedent identification. In this paper, a rich feature set including the innovative discourse features are employed so as to resolve those commonly-used Chinese pronouns in modem Chinese written texts. Moreover, a maximum-entropy based model is presented to estimate the confidence for each antecedent candidate. Experimental results show that our method achieves 83.5% success rate which is better than those obtained by rule-based and SVM-based methods.
URI: http://hdl.handle.net/11536/32531
ISBN: 978-3-540-85286-5
ISSN: 0302-9743
期刊: ADVANCES IN NATURAL LANGUAGE PROCESSING, PROCEEDINGS
Volume: 5221
起始頁: 296
結束頁: 302
Appears in Collections:Conferences Paper