In this paper, we explore how to leverage different types of knowledge to better resolve pronoun coreference with a neural model.
even though our model outperforms the End2end model by 22.7 F1 from i2b2 to CoNLL, its overall performance is still poor, which might be explained by that the i2b2 is an in-domain dataset and the knowledge contained in its training data is rarely useful for the general (news) domain dataset.