How does Turkish NLP work?
- Tokenization. Tokenization is the process of breaking text into smaller units, such as words or phrases, which allows better analysis and understanding of the structure of the Turkish language.
- Morphological Analysis. This method involves analyzing the structure of words in Turkish, including prefixes, suffixes, and roots, to understand their meanings and grammatical roles.
- Named Entity Recognition (NER). NER is a technique used to identify and categorize key information in text, such as names of people, organizations, and locations, which is crucial for extracting meaningful data from Turkish documents.
- Sentiment Analysis. Sentiment analysis involves determining the emotional tone behind a body of text, helping businesses to understand customer opinions and feedback in the Turkish language.