How does Shona NLP work?
- Tokenization. Tokenization involves breaking down text into individual words or phrases, allowing for easier analysis and processing of the language.
- Part-of-Speech Tagging. This method assigns parts of speech to each token, helping the system understand the grammatical structure of sentences.
- Named Entity Recognition. Named Entity Recognition identifies and classifies key elements in the text, such as names, locations, and dates, which are crucial for understanding context.
- Sentiment Analysis. Sentiment analysis assesses the emotional tone behind a series of words, which can provide insights into opinions and attitudes expressed in Shona texts.