Anaphora resolution by antecedent identification followed by anaphoricity determination

Ryu Iida, Kentaro Inui, Yuji Matsumoto

研究成果: Review article査読

14 被引用数 (Scopus)

抄録

We propose a machine learning-based approach to noun-phrase anaphora resolution that combines the advantages of previous learning-based models while overcoming their drawbacks. Our anaphora resolution process reverses the order of the steps in the classification-then-search model proposed by Ng and Cardie [2002b], inheriting all the advantages of that model. We conducted experiments on resolving noun-phrase anaphora in Japanese. The results show that with the selection-then-classification-based modifications, our proposed model outperforms earlier learning-based approaches.

本文言語English
ページ(範囲)417-434
ページ数18
ジャーナルACM Transactions on Asian Language Information Processing
4
4
DOI
出版ステータスPublished - 2005 12 1
外部発表はい

ASJC Scopus subject areas

  • Computer Science(all)

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