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.
REF propose an unsupervised model which extracts hypernym relation for resloving definite NPs.
Resolving And Generating Definite Anaphora By Modeling Hypernymy Using Unlabeled Corpora
Conference On Computational Natural Language Learning CoNLL
Computer Science