The Analysis of Synonymy and Antonymy in Discourse Relations: An interpretable Modeling Approach
This work addresses a gap in discourse research for linguists and computational linguists by providing interpretable models, though it is incremental as it builds on existing corpus-based approaches.
The authors tackled the problem of understanding how lexical semantics, specifically synonymy and antonymy, contributes to signaling explicit and implicit discourse relations like contrast and concession in the PDTB corpus, and they proposed transparent and explainable computational models to analyze this.
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.