@inproceedings{gonzalez-corbelle-etal-2023-lessons,
title = "Some lessons learned reproducing human evaluation of a data-to-text system",
author = "Gonz{\'a}lez Corbelle, Javier and
Alonso, Jose and
Bugar{\'\i}n-Diz, Alberto",
editor = "Belz, Anya and
Popovi{\'c}, Maja and
Reiter, Ehud and
Thomson, Craig and
Sedoc, Jo{\~a}o",
booktitle = "Proceedings of the 3rd Workshop on Human Evaluation of NLP Systems",
month = sep,
year = "2023",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "https://aclanthology.org/2023.humeval-1.5",
pages = "49--68",
abstract = "This paper presents a human evaluation reproduction study regarding the data-to-text generation task. The evaluation focuses in counting the supported and contradicting facts generated by a neural data-to-text model with a macro planning stage. The model is tested generating sport summaries for the ROTOWIRE dataset. We first describe the approach to reproduction that is agreed in the context of the ReproHum project. Then, we detail the entire configuration of the original human evaluation and the adaptations that had to be made to reproduce such an evaluation. Finally, we compare the reproduction results with those reported in the paper that was taken as reference.",
}
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<abstract>This paper presents a human evaluation reproduction study regarding the data-to-text generation task. The evaluation focuses in counting the supported and contradicting facts generated by a neural data-to-text model with a macro planning stage. The model is tested generating sport summaries for the ROTOWIRE dataset. We first describe the approach to reproduction that is agreed in the context of the ReproHum project. Then, we detail the entire configuration of the original human evaluation and the adaptations that had to be made to reproduce such an evaluation. Finally, we compare the reproduction results with those reported in the paper that was taken as reference.</abstract>
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%0 Conference Proceedings
%T Some lessons learned reproducing human evaluation of a data-to-text system
%A González Corbelle, Javier
%A Alonso, Jose
%A Bugarín-Diz, Alberto
%Y Belz, Anya
%Y Popović, Maja
%Y Reiter, Ehud
%Y Thomson, Craig
%Y Sedoc, João
%S Proceedings of the 3rd Workshop on Human Evaluation of NLP Systems
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F gonzalez-corbelle-etal-2023-lessons
%X This paper presents a human evaluation reproduction study regarding the data-to-text generation task. The evaluation focuses in counting the supported and contradicting facts generated by a neural data-to-text model with a macro planning stage. The model is tested generating sport summaries for the ROTOWIRE dataset. We first describe the approach to reproduction that is agreed in the context of the ReproHum project. Then, we detail the entire configuration of the original human evaluation and the adaptations that had to be made to reproduce such an evaluation. Finally, we compare the reproduction results with those reported in the paper that was taken as reference.
%U https://aclanthology.org/2023.humeval-1.5
%P 49-68
Markdown (Informal)
[Some lessons learned reproducing human evaluation of a data-to-text system](https://aclanthology.org/2023.humeval-1.5) (González Corbelle et al., HumEval-WS 2023)
ACL