A Ranking Approach to Chinese Coreference Resolution Based on Pairwise Classification Confidence
Wenbo Li · Zhongwen xinxi xuebao · 2007
As a typical phenomenon in language,coreference entails vital attention to be resolved in nature language processing.We describe a novel algorithm,which integrates global-evaluated confidence in classification in order to make sure that those pairs which high confidence take high priority in the clustering procedure.The experiments,under supervised learning framework both isolated and joint,show significant gains of the coreference resolution sy-stem.