Copy the page URI to the clipboard
Mellish, Chris; Scott, Donia; Cahill, Lynn; Paiva, Daniel; Evans, Roger and Reape, Mike
(2006).
DOI: https://doi.org/10.1017/S1351324906004104
URL: http://mcs.open.ac.uk/ds5473/publications/rags-JNL...
Abstract
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.