@inproceedings{35072e0f0a834788adea2269c44cc6ce,
title = "Story Cloze Task: UW NLP System",
abstract = "This paper describes University of Washington NLP{\textquoteright}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).",
author = "Roy Schwartz and Maarten Sap and Ioannis Konstas and Leila Zilles and Yejin Choi and Smith, {Noah A.}",
note = "Publisher Copyright: {\textcopyright} 2017 Association for Computational Linguistics; 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-Level Semantics, LSDSem 2017 ; Conference date: 03-04-2017",
year = "2017",
language = "الإنجليزيّة",
series = "LSDSem 2017 - 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-Level Semantics, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "52--55",
booktitle = "LSDSem 2017 - 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-Level Semantics, Proceedings of the Workshop",
address = "الولايات المتّحدة",
}