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arXiv · 2011.03992

A Gold Standard Methodology for Evaluating Accuracy in Data-To-Text Systems

Craig Thomson·Ehud Reiter
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Abstract

Most Natural Language Generation systems need to produce accurate texts. We propose a methodology for high-quality human evaluation of the accuracy of generated texts, which is intended to serve as a gold-standard for accuracy evaluations of data-to-text systems. We use our methodology to evaluate the accuracy of computer generated basketball summaries. We then show how our gold standard evaluation can be used to validate automated metrics

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Craig Thomson, Ehud Reiter. 2020-11-08. A Gold Standard Methodology for Evaluating Accuracy in Data-To-Text Systems. https://arxiv.org/abs/2011.03992

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