Previous work<cite> (Wiseman et al., 2017)</cite> notices the problem and proposes an extractive metric to evaluate the consistency between the generation and its input structured data. However, such consistency is not involved in the training process to guide model learning. In this paper, we propose to use a new training framework that directly incorporates consistency verification to guide the generation during the training process.