Automatic detection of Russia-Ukraine war euphemisms

Automatic detection of figurative language is one of the major directions in modern NLP. Euphemisms are words or phrases used to mitigate the expression. By and large, they are socially and culturally determined, naming the sensitive entities in an indirect, softened way. The problems of the automatic detection of euphemisms arise when words can be used both literally (non-euphemistically) and euphemistically. We refer to such usages as PETs (potentially euphemistic terms). The attempts to detect/disambiguate euphemisms cross-linguistically have reported a high performance of transformer-based neural models. Nonetheless, such models have not been tested on Ukrainian datasets. The purpose of this endeavor is to test LLMs on the collected, annotated, and processed Ukrainian dataset, exemplified in this paper by the newly coined during the Russia-Ukraine war PETs. Employing prompt engineering, the study has revealed a high performance of GPT-4o and GPT-4o-mini on the Ukrainian PET dataset.