A PROBLEM SOLVING APPROACH TO GENERATING TEXT FROM SYSTEMIC GRAMMARS


Systemic grammar has been used for AI text generation work in the past, but the implementations have tended be ad hoc or inefficient. This paper presents an approach to systemic text generation where AI problem solving techniques are applied directly to an unadulterated systemic grammar. This approach is made possible by a special relationship between systemic grammar and problem solving: both are organized primarily as choosing from alternatives. The result is simple, efficient text generation firmly based in a linguistic theory. 
