The E2E Dataset: New Challenges For End-to-End Generation
Jekaterina Novikova, Ondřej Dušek, Verena Rieser · 2017
This paper describes the E2E data, a new dataset for training end-to-end, datadriven 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.