The Analysis of Synonymy and Antonymy in Discourse Relations: An Interpretable Modeling Approach

Asela Reig Alamillo, David Torres Moreno, Eliseo Morales González, Mauricio Toledo Acosta, Antoine Taroni, Jorge Hermosillo Valadez


Abstract
The idea that discourse relations are interpreted both by explicit content and by shared knowledge between producer and interpreter is pervasive in discourse and linguistic studies. How much weight should be ascribed in this process to the lexical semantics of the arguments is, however, uncertain. We propose a computational approach to analyze contrast and concession relations in the PDTB corpus. Our work sheds light on the question of how much lexical relations contribute to the signaling of such explicit and implicit relations, as well as on the contribution of different parts of speech to these semantic relations. This study contributes to bridging the gap between corpus and computational linguistics by proposing transparent and explainable computational models of discourse relations based on the synonymy and antonymy of their arguments.
Anthology ID:
2023.cl-2.6
Volume:
Computational Linguistics, Volume 49, Issue 2 - June 2023
Month:
June
Year:
2023
Address:
Cambridge, MA
Venue:
CL
SIG:
Publisher:
MIT Press
Note:
Pages:
429–464
Language:
URL:
https://aclanthology.org/2023.cl-2.6
DOI:
10.1162/coli_a_00477
Bibkey:
Cite (ACL):
Asela Reig Alamillo, David Torres Moreno, Eliseo Morales González, Mauricio Toledo Acosta, Antoine Taroni, and Jorge Hermosillo Valadez. 2023. The Analysis of Synonymy and Antonymy in Discourse Relations: An Interpretable Modeling Approach. Computational Linguistics, 49(2):429–464.
Cite (Informal):
The Analysis of Synonymy and Antonymy in Discourse Relations: An Interpretable Modeling Approach (Reig Alamillo et al., CL 2023)
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PDF:
https://aclanthology.org/2023.cl-2.6.pdf