896

It was motivated by two difficulties in scaling up existing generators. Current generators only accept input that are relatively poor in information, such as feature structures or lists of propositions; they are unable to deal with input rich in information, as one might expect from, for example, an expert system with a complete model of its domain or a natural language understander with good inference ability. Current generators also have a very restricted knowledge of language-- indeed, they succeed largely because they have few syntactic or lexical options available (McDonald 1987)-- and they are unable to cope with more knowledge because they deal with interactions among the various possible choices only as special cases. An utterance is simply the result of successive word choices. The treatment of syntax in connectionist and spreading activation systems is a well-known problem.