How does Tatar NLP work?
- Tokenization. Tokenization is the process of breaking text into individual words or phrases called tokens, which helps in analyzing the structure of Tatar sentences.
- Sentiment Analysis. Sentiment analysis involves determining the emotional tone behind a series of words, useful for understanding opinions expressed in Tatar texts.
- Machine Translation. Machine translation automatically translates text from Tatar to other languages and vice versa, facilitating cross-linguistic communication.
- Named Entity Recognition. Named entity recognition identifies and classifies key entities in texts, such as names, organizations, or locations, enhancing information extraction from Tatar content.