@InProceedings{schwartz-EtAl:2017:LSDSem,
  author    = {Schwartz, Roy  and  Sap, Maarten  and  Konstas, Ioannis  and  Zilles, Leila  and  Choi, Yejin  and  Smith, Noah A.},
  title     = {Story Cloze Task: UW NLP System},
  booktitle = {Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {52--55},
  abstract  = {This paper describes University of Washington NLP’s submission for the
	Linking Models of Lexical, Sentential and Discourse-level Semantics (LSDSem
	2017) shared task—the Story Cloze Task. Our system is a linear classifier
	with a variety of features, including both the scores of a neural language
	model and style features. We report 75.2% accuracy on the task. A further
	discussion of our results can be found in Schwartz et al. (2017).},
  url       = {http://aclweb.org/anthology/W17-0907}
}