How does Macedonian NLP work?
- Tokenization. Tokenization splits text into individual words or tokens, making it easier to analyze the structure of sentences in the Macedonian language.
- Part-of-Speech Tagging. This method assigns parts of speech to each token, helping to understand the grammatical structure and meaning of sentences.
- Named Entity Recognition. Named Entity Recognition identifies and classifies key entities in text, such as names, organizations, and locations within Macedonian texts.
- Sentiment Analysis. Sentiment Analysis assesses the emotional tone behind words, helping to determine the sentiment expressed in Macedonian language inputs.