E2E NLG ChallengeMotivation Natural language generation plays a critical role for Conversational Agents as it has a significant impact on a user’s impression of the system. This shared task focuses on recent end-to-end (E2E), data-driven NLG methods, which jointly learn sentence planning and surface realisation from non-aligned data, e.g. (Wen et al., 2015; Mei et al., 2016; Dusek and Jurcicek, 2016; Lampouras and
