@InProceedings{choubey-huang:2017:EMNLP20172,
  author    = {Choubey, Prafulla Kumar  and  Huang, Ruihong},
  title     = {Event Coreference Resolution by Iteratively Unfolding Inter-dependencies among Events},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {2124--2133},
  abstract  = {We introduce a novel iterative approach for event coreference resolution that
	gradually builds event clusters by exploiting inter-dependencies among event
	mentions within the same chain as well as across event chains. Among event
	mentions in the same chain, we distinguish within- and cross-document event
	coreference links by using two distinct pairwise classifiers, trained
	separately to capture differences in feature distributions of within- and
	cross-document event clusters. Our event coreference approach alternates
	between WD and CD clustering and combines arguments from both event clusters
	after every merge, continuing till no more merge can be made. And then it
	performs further merging between event chains that are both closely related to
	a set of other chains of events. Experiments on the ECB+ corpus show that our
	model outperforms state-of-the-art methods in joint task of WD and CD event
	coreference resolution.},
  url       = {https://www.aclweb.org/anthology/D17-1226}
}