@InProceedings{dekok-EtAl:2017:EACLshort,
  author    = {de Kok, Dani\"{e}l  and  Ma, Jianqiang  and  Dima, Corina  and  Hinrichs, Erhard},
  title     = {PP Attachment: Where do We Stand?},
  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     = {311--317},
  abstract  = {Prepostitional phrase (PP) attachment is a well known challenge to parsing. In
	this paper, we combine
	the insights of different works, namely: (1) treating PP attachment as a
	classification task with an arbitrary number of attachment candidates; (2) 
	using auxiliary distributions to augment the data beyond the hand-annotated
	training set; (3)  using topological fields to get information about the
	distribution of PP attachment throughout clauses and (4) using state-of-the-art
	techniques such as word embeddings and neural networks. We show that jointly
	using these techniques leads to substantial improvements. We also conduct a
	qualitative analysis to gauge where the ceiling of the task is in a realistic
	setup.},
  url       = {http://www.aclweb.org/anthology/E17-2050}
}