Resolving and generating definite anaphora by modeling hypernymy using unlabeled corpora

Abstract

We demonstrate an original and successful approach for both resolving and generating definite anaphora. We propose and evaluate unsupervised models for extracting hypernym relations by mining cooccurrence data of definite NPs and potential antecedents in an unlabeled corpus. The algorithm outperforms a standard WordNet-based approach to resolving and generating definite anaphora. It also substantially outperforms recent related work using pattern-based extraction of such hypernym relations for coreference resolution. © 2006 Association for Computational Linguistics.