Best practices for the human evaluation of automatically generated text
Proceedings of the 12th International Conference on Natural Language …, 2019•aclanthology.org
Currently, there is little agreement as to how Natural Language Generation (NLG) systems
should be evaluated. While there is some agreement regarding automatic metrics, there is a
high degree of variation in the way that human evaluation is carried out. This paper provides
an overview of how human evaluation is currently conducted, and presents a set of best
practices, grounded in the literature. With this paper, we hope to contribute to the quality and
consistency of human evaluations in NLG.
should be evaluated. While there is some agreement regarding automatic metrics, there is a
high degree of variation in the way that human evaluation is carried out. This paper provides
an overview of how human evaluation is currently conducted, and presents a set of best
practices, grounded in the literature. With this paper, we hope to contribute to the quality and
consistency of human evaluations in NLG.
Abstract
Currently, there is little agreement as to how Natural Language Generation (NLG) systems should be evaluated. While there is some agreement regarding automatic metrics, there is a high degree of variation in the way that human evaluation is carried out. This paper provides an overview of how human evaluation is currently conducted, and presents a set of best practices, grounded in the literature. With this paper, we hope to contribute to the quality and consistency of human evaluations in NLG.
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