Turkish Delights: a Dataset on Turkish Euphemisms

TL;DR

This paper introduces the first Turkish euphemism dataset, enabling NLP research on figurative language in Turkish, and evaluates transformer models for euphemism detection.

Contribution

It provides a novel Turkish euphemism dataset with annotations and benchmarks transformer models for euphemism detection in Turkish.

Findings

Transformer models achieve promising detection accuracy.

The dataset enables future NLP research on Turkish euphemisms.

Benchmark results establish baseline performance for the task.

Abstract

Euphemisms are a form of figurative language relatively understudied in natural language processing. This research extends the current computational work on potentially euphemistic terms (PETs) to Turkish. We introduce the Turkish PET dataset, the first available of its kind in the field. By creating a list of euphemisms in Turkish, collecting example contexts, and annotating them, we provide both euphemistic and non-euphemistic examples of PETs in Turkish. We describe the dataset and methodologies, and also experiment with transformer-based models on Turkish euphemism detection by using our dataset for binary classification. We compare performances across models using F1, accuracy, and precision as evaluation metrics.