@InProceedings{braud-lacroix-sogaard:2017:EMNLP2017,
  author    = {Braud, Chlo\'{e}  and  Lacroix, Oph\'{e}lie  and  S{\o}gaard, Anders},
  title     = {Does syntax help discourse segmentation? Not so much},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {2432--2442},
  abstract  = {Discourse segmentation is the first step in building discourse parsers. Most
	work on discourse segmentation does not scale to real-world discourse parsing
	across languages, for two reasons: (i) models rely on constituent trees, and
	(ii) experiments have relied on gold standard identification of sentence and
	token boundaries. We therefore investigate to what extent constituents can be
	replaced with universal dependencies, or left out completely, as well as how
	state-of-the-art segmenters fare in the absence of sentence boundaries. Our
	results show that dependency information is less useful than expected, but we
	provide a fully scalable, robust model that only relies on part-of-speech
	information, and show that it performs well across languages in the absence of
	any gold-standard annotation.},
  url       = {https://www.aclweb.org/anthology/D17-1258}
}