Exploiting syntactic patterns as clues in zero-anaphora resolution

Abstract

We approach the zero-anaphora resolution problem by decomposing it into intra-sentential and inter-sentential zeroanaphora resolution. For the former problem, syntactic patterns of the appearance of zero-pronouns 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 intra-sentential zero-anaphora, which consequently improves the overall performance of zeroanaphora resolution. © 2006 Association for Computational Linguistics.