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A Reference Architecture for Generation Systems

Published online by Cambridge University Press:  11 October 2004

CHRIS MELLISH ,
MIKE REAPE ,
DONIA SCOTT ,
LYNNE CAHILL ,
ROGER EVANS  and
DANIEL PAIVA
CHRIS MELLISH
Affiliation:
School of Informatics, University of Edinburgh, Appleton Tower, Crichton St, Edinburgh, UK e-mail: [email protected]
MIKE REAPE
Affiliation:
School of Informatics, University of Edinburgh, Appleton Tower, Crichton St, Edinburgh, UK e-mail: [email protected]
DONIA SCOTT
Affiliation:
Information Technology Research Institute, University of Brighton, Lewes Rd, Brighton, UK e-mail: http://www.itri.brighton.ac.uk/rags
LYNNE CAHILL
Affiliation:
Information Technology Research Institute, University of Brighton, Lewes Rd, Brighton, UK e-mail: http://www.itri.brighton.ac.uk/rags
ROGER EVANS
Affiliation:
Information Technology Research Institute, University of Brighton, Lewes Rd, Brighton, UK e-mail: http://www.itri.brighton.ac.uk/rags
DANIEL PAIVA
Affiliation:
Information Technology Research Institute, University of Brighton, Lewes Rd, Brighton, UK e-mail: http://www.itri.brighton.ac.uk/rags
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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.

Type
Papers
Information
Natural Language Engineering , Volume 10 , Issue 3-4 , September 2004 , pp. 227 - 260
Copyright
© 2004 Cambridge University Press

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