Story Cloze Task: UW NLP System
2017-04-01WS 2017Unverified0· sign in to hype
Roy Schwartz, Maarten Sap, Ioannis Konstas, Leila Zilles, Yejin Choi, Noah A. Smith
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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).