This paper mainly focuses on the research of using anaphoricity identification and global optimization to improve the coreference resolution. By using coreference determination result feedback and tunable parameter, the coreference resolution can combine with different anaphoricity identification.We treat the anaphoricity identification as a classification problem, and apply maximum entropy model and 70 features to build
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