Unsupervised Ranking Model for Entity Coreference Resolution
2016-03-15NAACL 2016Unverified0· sign in to hype
Xuezhe Ma, Zhengzhong Liu, Eduard Hovy
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Coreference resolution is one of the first stages in deep language understanding and its importance has been well recognized in the natural language processing community. In this paper, we propose a generative, unsupervised ranking model for entity coreference resolution by introducing resolution mode variables. Our unsupervised system achieves 58.44% F1 score of the CoNLL metric on the English data from the CoNLL-2012 shared task (Pradhan et al., 2012), outperforming the Stanford deterministic system (Lee et al., 2013) by 3.01%.