Unsupervised models for coreference resolution
Vincent Ng · 2008
We present a generative model for unsupervised coreference resolution that views coreference as an EM clustering process. For comparison purposes, we revisit Haghighi and Klein's (2007) fully-generative Bayesian model for unsupervised coreference resolution, discuss its potential weaknesses and consequently propose three modifications to their model. Experimental results on the ACE data sets show that our model outperforms their original model by a large margin and compares favorably to the modified model.