  The process of microplanning encompasses a range of problems in Natural
Language Generation (NLG), such as referring expression generation, lexical
choice, and aggregation, problems in which a generator must bridge underlying
domain-specific representations and general linguistic representations. In this
paper, we describe a uniform approach to microplanning based on declarative
representations of a generator's communicative intent. These representations
describe the results of NLG: communicative intent associates the concrete
linguistic structure planned by the generator with inferences that show how the
meaning of that structure communicates needed information about some
application domain in the current discourse context. Our approach, implemented
in the SPUD (sentence planning using description) microplanner, uses the
lexicalized tree-adjoining grammar formalism (LTAG) to connect structure to
meaning and uses modal logic programming to connect meaning to context. At the
same time, communicative intent representations provide a resource for the
process of NLG. Using representations of communicative intent, a generator can
augment the syntax, semantics and pragmatics of an incomplete sentence
simultaneously, and can assess its progress on the various problems of
microplanning incrementally. The declarative formulation of communicative
intent translates into a well-defined methodology for designing grammatical and
conceptual resources which the generator can use to achieve desired
microplanning behavior in a specified domain.
