@InProceedings{gritta-EtAl:2017:Long,
  author    = {Gritta, Milan  and  Pilehvar, Mohammad Taher  and  Limsopatham, Nut  and  Collier, Nigel},
  title     = {Vancouver Welcomes You! Minimalist Location Metonymy Resolution},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {1248--1259},
  abstract  = {Named entities are frequently used in a metonymic manner. They serve as
	references to related entities such as people and organisations. Accurate
	identification and interpretation of metonymy can be directly beneficial to
	various NLP applications, such as Named Entity Recognition and Geographical
	Parsing. Until now, metonymy resolution (MR) methods mainly relied on parsers,
	taggers, dictionaries, external word lists and other handcrafted lexical
	resources. We show how a minimalist neural approach combined with a novel
	predicate window method can achieve competitive results on the SemEval 2007
	task on Metonymy Resolution. Additionally, we contribute with a new
	Wikipedia-based MR dataset called RelocaR, which is tailored towards locations
	as well as improving previous deficiencies in annotation guidelines.},
  url       = {http://aclweb.org/anthology/P17-1115}
}