E2E NLG Challenge: Neural Models vs. Templates

Code

• github.com/UKPLab/e2e-nlg-challenge-2017
  In paperpytorch★ 0

Abstract

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 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.

Tasks

Reproductions