@InProceedings{bekoulis-EtAl:2017:EACLshort,
  author    = {Bekoulis, Giannis  and  Deleu, Johannes  and  Demeester, Thomas  and  Develder, Chris},
  title     = {Reconstructing the house from the ad: Structured prediction on real estate classifieds},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {274--279},
  abstract  = {In this paper, we address the (to the best of our knowledge) new problem of
	extracting a structured description of real estate properties from their
	natural language descriptions in classifieds. We survey and present several
	models to (a) identify important entities of a property (e.g.,rooms) from
	classifieds and (b) structure them into a tree format, with the entities as
	nodes and edges representing a part-of relation. Experiments show that a
	graph-based system deriving the tree from an initially fully connected entity
	graph, outperforms a transition-based system starting from only the entity
	nodes, since it better reconstructs the tree.},
  url       = {http://www.aclweb.org/anthology/E17-2044}
}