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A Reference Architecture for Natural Language Generation Systems

Published online by Cambridge University Press:  02 March 2006

CHRIS MELLISH ,
DONIA SCOTT ,
LYNNE CAHILL ,
DANIEL PAIVA ,
ROGER EVANS  and
MIKE REAPE
CHRIS MELLISH
Affiliation:
Department of Computing Science, University of Aberdeen, Aberdeen, UK
DONIA SCOTT
Affiliation:
Centre for Research in Computing, The Open University, Milton Keynes, UK
LYNNE CAHILL
Affiliation:
University of Sussex, UK
DANIEL PAIVA
Affiliation:
University of Sussex, UK
ROGER EVANS
Affiliation:
School of Maths and Computing, University of Brighton, Brighton, UK
MIKE REAPE
Affiliation:
School of Informatics, University of Edinburgh, Edinburgh, UK e-mail: rags@open.ac.uk
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Abstract

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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.

Information

Type
Papers
Information
Natural Language Engineering , Volume 12 , Issue 1 , March 2006 , pp. 1 - 34
Copyright
2006 Cambridge University Press

Footnotes

This is a revised and updated version of the paper “A Reference Architecture for Generation Systems” which appeared (in error) in Natural Language Engineering 10(3/4) the Special Issue on Software Architectures for Language Engineering. This version should be cited in preference to the earlier one.