Turkish Delights: a Dataset on Turkish Euphemisms
This work addresses a gap in natural language processing for Turkish language applications, but it is incremental as it extends existing computational methods to a new language.
The researchers tackled the understudied problem of euphemism detection in Turkish by creating the first Turkish PET dataset, and they experimented with transformer-based models for binary classification, reporting performance using F1, accuracy, and precision metrics.
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.