@InProceedings{zhang-litman-forbesriley:2016:COLING,
  author    = {Zhang, Fan  and  Litman, Diane  and  Forbes-Riley, Katherine},
  title     = {Inferring Discourse Relations from PDTB-style Discourse Labels for Argumentative Revision Classification},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {2615--2624},
  abstract  = {Penn Discourse Treebank (PDTB)-style annotation focuses on labeling local
	discourse relations between text spans and typically ignores larger discourse
	contexts. In this paper we propose two approaches to infer discourse relations
	in a  paragraph-level context from annotated PDTB labels.  We investigate the
	utility of inferring such discourse information using the task of revision
	classification. Experimental results demonstrate that the inferred information
	can significantly improve classification performance compared to baselines, not
	only when PDTB annotation comes from humans but also from automatic parsers.},
  url       = {http://aclweb.org/anthology/C16-1246}
}