When Semantic Overlap Is Not Enough: Cross-Lingual Euphemism Transfer Between Turkish and English

TL;DR

This paper explores cross-lingual transfer of euphemism detection between Turkish and English, revealing that semantic overlap alone does not ensure effective transfer, especially in low-resource settings, due to pragmatic and contextual differences.

Contribution

It introduces a categorization of euphemistic terms based on semantic and pragmatic overlap and analyzes transfer asymmetries in multilingual euphemism detection.

Findings

Semantic overlap is not sufficient for positive transfer.

Transfer performance can degrade in low-resource Turkish-to-English scenarios.

NOPET-based training can sometimes improve transfer despite lack of overlap.

Abstract

Euphemisms substitute socially sensitive expressions, often softening or reframing meaning, and their reliance on cultural and pragmatic context complicates modeling across languages. In this study, we investigate how cross-lingual equivalence influences transfer in multilingual euphemism detection. We categorize Potentially Euphemistic Terms (PETs) in Turkish and English into Overlapping (OPETs) and Non-Overlapping (NOPETs) subsets based on their functional, pragmatic, and semantic alignment. Our findings reveal a transfer asymmetry: semantic overlap is insufficient to guarantee positive transfer, particularly in low-resource Turkish-to-English direction, where performance can degrade even for overlapping euphemisms, and in some cases, improve under NOPET-based training. Differences in label distribution help explain these counterintuitive results. Category-level analysis suggests that transfer may be influenced by domain-specific alignment, though evidence is limited by sparsity.