@inproceedings{pascucci-tavosanis-2024-confronto,
title = "Confronto tra Diversi Tipi di Valutazione del Miglioramento della Chiarezza di Testi Amministrativi in Lingua Italiana",
author = "Pascucci, Mariachiara and
Tavosanis, Mirko",
editor = "Dell'Orletta, Felice and
Lenci, Alessandro and
Montemagni, Simonetta and
Sprugnoli, Rachele",
booktitle = "Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024)",
month = dec,
year = "2024",
address = "Pisa, Italy",
publisher = "CEUR Workshop Proceedings",
url = "https://aclanthology.org/2024.clicit-1.81/",
pages = "746--756",
language = "ita",
ISBN = "979-12-210-7060-6",
abstract = "The paper presents a comparison of different types of evaluation of administrative texts in the Italian language on which a clarity improvement intervention was carried out. The clarity improvement was performed by human experts and ChatGPT. The evaluation was carried out in four different ways: by expert evaluators, used as a reference; by evaluators with good skills, subject to dedicated training; by generic evaluators recruited through a crowdsourcing platform; by ChatGPT. The results show that the closest match to the results of the evaluation by expert evaluators was reached, by a wide margin, by evaluators with good skills and dedicated training; the second best approach was reached by requesting evaluation from ChatGPT; the worst approach was reached by generic evaluators recruited through a crowdsourcing platform. Task features that may have influenced the outcome are also discussed."
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<abstract>The paper presents a comparison of different types of evaluation of administrative texts in the Italian language on which a clarity improvement intervention was carried out. The clarity improvement was performed by human experts and ChatGPT. The evaluation was carried out in four different ways: by expert evaluators, used as a reference; by evaluators with good skills, subject to dedicated training; by generic evaluators recruited through a crowdsourcing platform; by ChatGPT. The results show that the closest match to the results of the evaluation by expert evaluators was reached, by a wide margin, by evaluators with good skills and dedicated training; the second best approach was reached by requesting evaluation from ChatGPT; the worst approach was reached by generic evaluators recruited through a crowdsourcing platform. Task features that may have influenced the outcome are also discussed.</abstract>
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%0 Conference Proceedings
%T Confronto tra Diversi Tipi di Valutazione del Miglioramento della Chiarezza di Testi Amministrativi in Lingua Italiana
%A Pascucci, Mariachiara
%A Tavosanis, Mirko
%Y Dell’Orletta, Felice
%Y Lenci, Alessandro
%Y Montemagni, Simonetta
%Y Sprugnoli, Rachele
%S Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024)
%D 2024
%8 December
%I CEUR Workshop Proceedings
%C Pisa, Italy
%@ 979-12-210-7060-6
%G ita
%F pascucci-tavosanis-2024-confronto
%X The paper presents a comparison of different types of evaluation of administrative texts in the Italian language on which a clarity improvement intervention was carried out. The clarity improvement was performed by human experts and ChatGPT. The evaluation was carried out in four different ways: by expert evaluators, used as a reference; by evaluators with good skills, subject to dedicated training; by generic evaluators recruited through a crowdsourcing platform; by ChatGPT. The results show that the closest match to the results of the evaluation by expert evaluators was reached, by a wide margin, by evaluators with good skills and dedicated training; the second best approach was reached by requesting evaluation from ChatGPT; the worst approach was reached by generic evaluators recruited through a crowdsourcing platform. Task features that may have influenced the outcome are also discussed.
%U https://aclanthology.org/2024.clicit-1.81/
%P 746-756
Markdown (Informal)
[Confronto tra Diversi Tipi di Valutazione del Miglioramento della Chiarezza di Testi Amministrativi in Lingua Italiana](https://aclanthology.org/2024.clicit-1.81/) (Pascucci & Tavosanis, CLiC-it 2024)
ACL