How does Tajik NLP work?
- Tokenization. Tokenization involves breaking down text into smaller units, such as words or phrases, which are easier to analyze.
- Sentiment Analysis. Sentiment analysis assesses the emotional tone behind a series of words, helping to understand attitudes and opinions expressed in Tajik text.
- Named Entity Recognition (NER). NER identifies and classifies key entities in textual data, such as names, organizations, and locations within Tajik language content.
- Language Modeling. Language modeling involves predicting the likelihood of a sequence of words, facilitating tasks like text generation and completion in Tajik.