Applying Correlation Clustering to Chinese Noun Phrase Coreference Resolution
Yuan Li · 2007
Coreference resolution plays an important role in natural language processing. In this paper, coreference resolution is converted to a graph clustering problem firstly, and then correlation clustering is used for automatic graph clustering. Compared with the traditional clustering approaches: link-first and link-best, the proposed algorithm takes the relations among the NPs into account sufficiently. In addition, it does not need to specify the desired number of clusters and a distance threshold. The experimental results on the ACE Chinese training corpus demonstrate that the proposed method of coreference is an effective one.