Evaluating an NLG system using post-editing

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4 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)1700-1701
Number of pages2
JournalIJCAI International Joint Conference on Artificial Intelligence
Publication statusPublished - 1 Dec 2005
Event19th International Joint Conference on Artificial Intelligence, IJCAI 2005 - Edinburgh, United Kingdom
Duration: 30 Jul 20055 Aug 2005

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