Learning to perform these tasks jointly is challenging due to the ambiguity in deciding which records are relevant, the complex dependencies between selected records, and the multiple ways in which these records can be described. Previous work has made significant progress on this task (Chen and Mooney, 2008;<cite> Angeli et al., 2010</cite>; Konstas and Lapata, 2012) . However, most approaches solve the two content selection and surface realization subtasks separately, use manual domain-dependent resources (e.g., semantic parsers) and features, or employ template-based generation.