Turkish Text

Research on Turkish text focuses on developing and adapting natural language processing (NLP) techniques to this morphologically rich language, addressing challenges posed by its agglutinative nature and relatively limited resources compared to English. Current efforts concentrate on creating and improving Turkish language models, often based on transformer architectures like BERT and its variants, for tasks such as text classification, question answering, and machine translation, as well as developing specialized datasets for these tasks. This work is significant for advancing NLP capabilities in low-resource languages and has practical implications for various applications, including educational technology, legal tech, and social media analysis.