Text and knowledge mining for coreference resolution
NAACL '01: Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies（2001）
摘要
Traditionally coreference is resolved by satisfying a combination of salience, syntactic, semantic and discourse constraints. The acquisition of such knowledge is time-consuming, difficult and error-prone. Therefore, we present a knowledge minimalist methodology of mining coreference rules from annotated text corpora. Semantic consistency evidence, which is a form of knowledge required by coreference, is easily retrieved from WordNet. Additional consistency knowledge is discovered by a meta-bootstrapping algorithm applied to unlabeled texts.
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关键词
discourse constraint,annotated text corpus,mining coreference rule,knowledge mining,semantic consistency evidence,meta-bootstrapping algorithm,coreference resolution,unlabeled text,additional consistency knowledge,knowledge minimalist methodology,satisfiability
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