  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%.
