How does Sinhala NLP work?
- Tokenization. This method involves breaking down Sinhala text into smaller components such as words or phrases, making it easier to analyze and process.
- Part-of-Speech Tagging. This technique assigns parts of speech to each token in a sentence, helping machines understand the grammatical structure of the Sinhala language.
- Named Entity Recognition. This process identifies and classifies entities such as names, organizations, and locations within Sinhala text, allowing for better information extraction.
- Sentiment Analysis. This method evaluates the emotional tone behind Sinhala text, helping to determine the sentiment expressed within a given piece of content.
