Story Cloze Task: UW NLP System
Roy Schwartz, Maarten Sap, Ioannis Konstas, Leila Zilles, Yejin Choi, Noah A. Smith · 2017
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).