Zero-anaphora resolution by learning rich syntactic pattern features

Ryu Iida, Kentaro Inui, Yuji Matsumoto

研究成果: Article査読

27 被引用数 (Scopus)

抄録

We approach the zero-anaphora resolution problem by decomposing it into intrasentential and intersentential zero-anaphora resolution tasks. For the former task, syntactic patterns of zeropronouns and their antecedents are useful clues. Taking Japanese as a target language, we empirically demonstrate that incorporating rich syntactic pattern features in a state-of-the-art learning-based anaphora resolution model dramatically improves the accuracy of intrasentential zero-anaphora, which consequently improves the overall performance of zero-anaphora resolution.

本文言語English
論文番号12
ジャーナルACM Transactions on Asian Language Information Processing
6
4
DOI
出版ステータスPublished - 2007 12 1
外部発表はい

ASJC Scopus subject areas

  • Computer Science(all)

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