Computational Intelligence 8(1), 1992.
Abstract: Looking to the future, generators will have more knowledge of language and will have to deal with inputs which are very rich in information. As a result, several problems will become more acute, including selecting what to say at the sub-proposition level and dealing with interaction among goals and dependencies among choices. This paper explains how these problems arise and why they are hard to handle within traditional architectures for generation. It also discusses why these issues have not been well addressed; reasons include the current lack of demanding applications, undue respect for linguistic traditions, the use of reverse engineering to determine generator inputs, and the tendency to research only one issue at a time.