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.
|Number of pages||2|
|Journal||IJCAI International Joint Conference on Artificial Intelligence|
|Publication status||Published - 1 Dec 2005|
|Event||19th International Joint Conference on Artificial Intelligence, IJCAI 2005 - Edinburgh, United Kingdom|
Duration: 30 Jul 2005 → 5 Aug 2005