E2E NLG Challenge: Neural Models vs. Templates
Yevgeniy Puzikov, Iryna Gurevych · 2018
E2E NLG Challenge is a shared task on generating restaurant descriptions from sets of key-value pairs.This paper describes the results of our participation in the challenge.We develop a simple, yet effective neural encoder-decoder model 1 which produces fluent restaurant descriptions and outperforms a strong baseline.We further analyze the data provided by the organizers and conclude that the task can also be approached with a template-based model developed in just a few hours.