How does Myanmar Named Entity Recognition work?
- Tokenization. Tokenization involves breaking down text into smaller units, or tokens, which can be words or phrases essential for further analysis.
- Part-of-Speech Tagging. This method assigns parts of speech to each token, aiding the identification of proper nouns and other entities.
- Named Entity Classification. In this step, tokens identified as named entities are classified into defined categories such as person names, organizations, locations, etc.
- Rule-Based and Machine Learning Approaches. NER can utilize both rule-based systems, relying on predefined linguistic rules, and machine learning techniques that learn patterns from large datasets.
