@InProceedings{schenk-chiarcos:2017:LSDSem,
  author    = {Schenk, Niko  and  Chiarcos, Christian},
  title     = {Resource-Lean Modeling of Coherence in Commonsense Stories},
  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     = {68--73},
  abstract  = {We present a resource-lean neural recognizer for modeling coherence in
	commonsense stories. Our lightweight system is inspired by successful attempts
	to modeling discourse relations and stands out due to its simplicity and easy
	optimization compared to prior approaches to narrative script learning. 
	We evaluate our approach in the Story Cloze Test demonstrating an absolute
	improvement in accuracy of 4.7% over state-of-the-art implementations.},
  url       = {http://aclweb.org/anthology/W17-0910}
}