@InProceedings{mirza-tonelli:2016:COLING2,
  author    = {Mirza, Paramita  and  Tonelli, Sara},
  title     = {On the contribution of word embeddings to temporal relation classification},
  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     = {2818--2828},
  abstract  = {Temporal relation classification is a challenging task, especially when there
	are no explicit markers to characterise the relation between temporal entities.
	This occurs frequently in inter-sentential relations, whose entities are not
	connected via direct syntactic relations making classification even more
	difficult. In these cases, resorting to features that focus on the semantic
	content of the event words may be very beneficial for inferring implicit
	relations. Specifically, while morpho-syntactic and context features are
	considered sufficient for classifying event-timex pairs, we believe that
	exploiting distributional semantic information about event words can benefit
	supervised classification of other types of pairs. In this work, we assess the
	impact of using word embeddings as features for event words in classifying
	temporal relations of event-event pairs and event-DCT (document creation time)
	pairs.},
  url       = {http://aclweb.org/anthology/C16-1265}
}