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Augustine of Hippo at SemEval-2023 Task 4: An Explainable Knowledge Extraction Method to Identify Human Values in Arguments with SuperASKE

Alfio Ferrara, Sergio Picascia, Elisabetta Rocchetti


Abstract
In this paper we present and discuss the results achieved by the “Augustine of Hippo” team at SemEval-2023 Task 4 about human value detection. In particular, we provide a quantitative and qualitative reviews of the results obtained by SuperASKE, discussing respectively performance metrics and classification errors. Finally, we present our main contribution: an explainable and unsupervised approach mapping arguments to concepts, followed by a supervised classification model mapping concepts to human values.
Anthology ID:
2023.semeval-1.143
Volume:
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1044–1053
Language:
URL:
https://aclanthology.org/2023.semeval-1.143
DOI:
10.18653/v1/2023.semeval-1.143
Bibkey:
Cite (ACL):
Alfio Ferrara, Sergio Picascia, and Elisabetta Rocchetti. 2023. Augustine of Hippo at SemEval-2023 Task 4: An Explainable Knowledge Extraction Method to Identify Human Values in Arguments with SuperASKE. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1044–1053, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Augustine of Hippo at SemEval-2023 Task 4: An Explainable Knowledge Extraction Method to Identify Human Values in Arguments with SuperASKE (Ferrara et al., SemEval 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.semeval-1.143.pdf
Video:
 https://aclanthology.org/2023.semeval-1.143.mp4