The RAGS project aims to develop a reference architecture for natural language generation, to facilitate modular development of NLG systams as well as evaluation of components, systems and algorithms.
Enabling Resource Sharing in Language Generation: An Abstract Reference Architecture
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The RAGS project aims to develop a reference architecture for natural language generation, to facilitate modular development of NLG systams as well as evaluation of components, systems and algorithms. This paper gives an overview of the proposed framework, describing an abstract data model with five levels of representation: Conceptual, Semantic, Rhetorical, Document and Syntactic. We report on a re-implementation of an existing system using the RAGS data model.