@InProceedings{savary-EtAl:2017:MWE2017,
  author    = {Savary, Agata  and  Ramisch, Carlos  and  Cordeiro, Silvio  and  Sangati, Federico  and  Vincze, Veronika  and  QasemiZadeh, Behrang  and  Candito, Marie  and  Cap, Fabienne  and  Giouli, Voula  and  Stoyanova, Ivelina  and  Doucet, Antoine},
  title     = {The PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions},
  booktitle = {Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017)},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {31--47},
  abstract  = {Multiword expressions (MWEs) are
	known as a “pain in the neck” for NLP
	due to their idiosyncratic behaviour.
	While some categories of MWEs have
	been addressed by many studies, verbal
	MWEs (VMWEs), such as to take a
	decision, to break one’s heart or to turn
	off, have been rarely modelled. This is
	notably due to their syntactic variability,
	which hinders treating them as “words
	with spaces”. We describe an initiative
	meant to bring about substantial progress
	in understanding, modelling and process-
	ing VMWEs. It is a joint effort, carried
	out within a European research network,
	to elaborate universal terminologies and
	annotation guidelines for 18 languages. Its
	main outcome is a multilingual 5-million-
	word annotated corpus which underlies a
	shared task on automatic identification of
	VMWEs. This paper presents the corpus
	annotation methodology and outcome, the
	shared task organisation and the results of
	the participating systems.},
  url       = {http://www.aclweb.org/anthology/W17-1704}
}