TOWARD AN INTEGRATED GENERATION APPROACH WITH TREE‐ADJOINING GRAMMARS
Karin Harbusch · Computational Intelligence · 1994
Natural‐language generationhas gained importance since AI systems have become more sophisticated and canned text can no longer serve the elaborate communicative tasks in such a system. In this paper, suggestions are presented to apply uniformly the formalism oftree‐adjoining grammar(TAG) for all tasks of natural‐language generation. Up to now plan‐based systems have been preferred for most of the processing during generation. Since the individual tasks of natural‐language generation are very different and complex; for example, the determination of the propositional structure of a text is described using the TAG formalism–extended byconstraintsandfeature descriptions(UCTAC). Nevertheless, this paper proposes basic ideas for the generalization of applying a grammar formalism to natural‐language generation in order to build an overall integrated system for natural‐language generation. Finally, advantages of such a uniform model are discussed.