Datasets play a crucial role in advancing NLP tasks by providing resources for training and evaluating models. These datasets serve as the foundation for developing models that can understand and generate human language. However, little research has been performed on creating datasets in low-resource languages, such as Turkish, compared to English. This research focuses on paraphrase datasets, which is a limited area of study in NLP. To the best of our knowledge, nine Turkish paraphrase datasets are available. Accordingly, we provide a comprehensive review of Turkish paraphrase datasets by examining their scope, design, and linguistic properties. The pros and cons of the datasets are discussed, including their size, variety, and domain coverage limitations. Suggestions are presented for a more diverse, large-scale, and expandable Turkish paraphrase corpora that could better represent the language’s linguistic richness.
Teker et al. (Tue,) studied this question.