Evaluating an NLG System using Post-Editing

被引：0

作者：

Sripada, Somayajulu G. ^{[1
]}

Reiter, Ehud ^{[1
]}

Hawizy, Lezan ^{[1
]}

机构：

[1] Univ Aberdeen, Dept Comp Sci, Aberdeen AB24 3UE, Scotland

来源：

19TH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI-05) | 2005年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：1700 / 1701

页数：2

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