Each sentence is specified by a unique set of features. Feature-based systems are among the most sophisticated generators built today. No feature-based multisentence generators have been built to date. None of these systems is in commercial use. It is safe to say that at the present time one can fairly easily build a single-purpose generator for any specific application, or with some difficulty adapt an existing sentence generator to the application, with acceptable results.
Lexical selection is one of the most difficult problems in generation.
At its simplest, this question involves selecting the most appropriate single word for a given unit of input. However, as soon as the semantic model approaches a realistic size, and as soon as the lexicon is large enough to permit alternative locutions , the problem becomes very complex. In some situation, one might have to choose among the phrases John's car, John's sports car, his speedster, the automobile, the red vehicle, the red Mazda for referring to a certain car. The decision depends on what has already been said, what is referentially available from context, what is most salient, what stylistic effect the speaker wishes to produce, and so on. At this time no general methods exist to perform lexical selection .