@InProceedings{arcan-mccrae-buitelaar:2016:COLING,
  author    = {Arcan, Mihael  and  McCrae, John Philip  and  Buitelaar, Paul},
  title     = {Expanding wordnets to new languages with multilingual sense disambiguation},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {97--108},
  abstract  = {Princeton WordNet is one of the most important resources for natural language
	processing, but is only available for English. While it has been translated
	using the expand approach to many other languages, this is an expensive manual
	process. Therefore it would be beneficial to have a high-quality automatic
	translation approach that would support NLP techniques, which rely on WordNet
	in new languages. The translation of wordnets is fundamentally complex because
	of the need to translate all senses of a word including low frequency senses,
	which is very challenging for current machine translation approaches. For this
	reason we leverage existing translations of WordNet in other languages to
	identify contextual information for wordnet senses from a large set of generic
	parallel corpora. We evaluate our approach using 10 translated wordnets for
	European languages. Our experiment shows a significant improvement over
	translation without any contextual information. Furthermore, we evaluate how
	the choice of pivot languages affects performance of multilingual word sense
	disambiguation.},
  url       = {http://aclweb.org/anthology/C16-1010}
}