We present the RAGS (Reference Architecture for Generation Systems) framework: a specification of an abstract Natural Language Generation (NLG) system architecture to support sharing, re-use, comparison and evaluation of NLG technologies. We argue that the evidence from a survey of actual NLG systems calls for a different emphasis in a reference proposal from that seen in similar initiatives in information extraction and multimedia interfaces. We introduce the framework itself, in particular the two-level data model that allows us to support the complex data requirements of NLG systems in a flexible and coherent fashion, and describe our efforts to validate the framework through a range of implementations.
Bibliographical note© 2006 Cambridge University Press
- Natural language generation systems
Mellish, C., Scott, D., Cahill, L., Evans, R., Paiva, D., & Reape, M. (2006). A reference architecture for natural language generation systems. Natural Language Engineering, 12(1), 1-34. https://doi.org/10.1017/S1351324906004104