@InProceedings{krageback-salomonsson:2016:CogALex-V,
  author    = {K\r{a}geb\"{a}ck, Mikael  and  Salomonsson, Hans},
  title     = {Word Sense Disambiguation using a Bidirectional LSTM},
  booktitle = {Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {51--56},
  abstract  = {In this paper we present a clean, yet effective, model for word sense
	disambiguation. 
	Our approach leverage a bidirectional long short-term memory network which is
	shared between all words. This enables the model to share statistical strength
	and to scale well with vocabulary size.
	The model is trained end-to-end, directly from the raw text to sense labels,
	and makes effective use of word order. 
	We evaluate our approach on two standard datasets, using identical
	hyperparameter settings, which are in turn tuned on a third set of held out
	data. 
	We employ no external resources (e.g. knowledge graphs, part-of-speech tagging,
	etc), language specific features, or hand crafted rules, but still achieve
	statistically equivalent results to the best state-of-the-art systems, that
	employ no such limitations.},
  url       = {http://aclweb.org/anthology/W16-5307}
}