@InProceedings{novikova-duvsek-rieser:2017:W17-55,
  author    = {Novikova, Jekaterina  and  Du\v{s}ek, Ond\v{r}ej  and  Rieser, Verena},
  title     = {The E2E Dataset: New Challenges For End-to-End Generation},
  booktitle = {Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue},
  month     = {August},
  year      = {2017},
  address   = {Saarbrücken, Germany},
  publisher = {Association for Computational Linguistics},
  pages     = {201--206},
  abstract  = {This paper describes the E2E data, a new dataset for training end-to-end,
	data-driven natural language generation systems in the restaurant domain, which
	is ten times bigger than existing, frequently used datasets in this area. The
	E2E dataset poses new challenges: (1) its human reference texts show more
	lexical richness and syntactic variation, including discourse phenomena; (2)
	generating from this set requires content selection. As such, learning from
	this dataset promises more natural, varied and less template-like system
	utterances. We also establish a baseline on this dataset, which illustrates
	some of the difficulties associated with this data.},
  url       = {http://aclweb.org/anthology/W17-5525}
}