@InProceedings{pilehvar-EtAl:2017:Long,
  author    = {Pilehvar, Mohammad Taher  and  Camacho-Collados, Jose  and  Navigli, Roberto  and  Collier, Nigel},
  title     = {Towards a Seamless Integration of Word Senses into Downstream NLP Applications},
  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     = {1857--1869},
  abstract  = {Lexical ambiguity can impede NLP systems from accurate understanding of
	semantics. Despite its potential benefits, the integration of sense-level
	information into NLP systems has remained understudied. By incorporating a
	novel disambiguation algorithm into a state-of-the-art classification model, we
	create a pipeline to integrate sense-level information into downstream NLP
	applications. We show that a simple disambiguation of the input text can lead
	to consistent performance improvement on multiple topic categorization and
	polarity detection datasets, particularly when the fine granularity of the
	underlying sense inventory is reduced and the document is sufficiently large.
	Our results also point to the need for sense representation research to focus
	more on in vivo evaluations which target the performance in downstream NLP
	applications rather than artificial benchmarks.},
  url       = {http://aclweb.org/anthology/P17-1170}
}