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

TL;DR

This paper introduces an interpretable computational model to analyze how lexical semantics, specifically synonymy and antonymy, influence explicit and implicit discourse relations in the PDTB corpus, bridging linguistics and computational methods.

Contribution

It presents a transparent, explainable approach to understanding the role of lexical semantics in discourse relations, focusing on contrast and concession signals.

Findings

Lexical semantics significantly contribute to discourse relation signaling.

Different parts of speech play distinct roles in explicit and implicit relations.

The model enhances interpretability in discourse analysis.

Abstract

The idea that discourse relations are construed through explicit content and shared, or implicit, knowledge between producer and interpreter is ubiquitous in discourse research and linguistics. However, the actual contribution of the lexical semantics of arguments is unclear. We propose a computational approach to the analysis of contrast and concession relations in the PDTB corpus. Our work sheds light on the extent to which lexical semantics contributes to signaling explicit and implicit discourse relations and clarifies the contribution of different parts of speech in both. This study contributes to bridging the gap between corpus linguistics and computational linguistics by proposing transparent and explainable models of discourse relations based on the synonymy and antonymy of their arguments.