An NPcluster based approach to coreference resolution

Traditionally, coreference resolution is done by mining the reference relationships between NP pairs. However, an individual NP usually lacks adequate description information of its referred entity. In this paper, we propose a supervised learning-based approach which does coreference resolution by exploring the relationships between NPs and coreferential clusters. Compared with individual NPs, coreferential clusters could pro-vide richer information of the entities for better rules learning and reference determination. The evaluation done on MEDLINE data set shows that our approach outperforms the baseline NP-NP based approach in both recall and precision.