Evaluating an NLG system using post-editing

Authors:
Somayajulu G. Sripada;Ehud Reiter;Lezan Hawizy
Affiliations:
Department of Computing Science, University of Aberdeen, Aberdeen, UK;Department of Computing Science, University of Aberdeen, Aberdeen, UK;Department of Computing Science, University of Aberdeen, Aberdeen, UK
Venue:
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Year:
2005

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HLT-NAACL-EDUC '03 Proceedings of the HLT-NAACL 03 workshop on Building educational applications using natural language processing - Volume 2

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Abstract

Computer-generated texts, whether from Natural Language Generation (NLG) or Machine Translation (MT) systems, are often post-edited by humans before being released to users. The frequency and type of post-edits is a measure of how well the system works, and can be used for evaluation. We describe how we have used post-edit data to evaluate SUMTIME-MOUSAM, an NLG system that produces weather forecasts.