  The rapid development and application of natural language generation (NLG)
techniques has revolutionized the field of automatic text production. However,
these techniques are still limited in their ability to produce human-like text
that is truly reasonable and informative. In this paper, we explore the
importance of NLG being guided by knowledge, in order to convey human-like
reasoning through language generation. We propose ten goals for intelligent NLG
systems to pursue, and briefly review the achievement of NLG techniques guided
by knowledge and reasoning. We also conclude by envisioning future directions
and challenges in the pursuit of these goals.
