How does Shona Named Entity Recognition work?
- Rule-based approaches. These methods use predefined linguistic rules and patterns to identify named entities in Shona text.
- Machine learning models. These models are trained on labeled Shona data to recognize entities, learning from examples to improve accuracy.
- Deep learning techniques. Using neural networks, deep learning models can capture complex patterns and provide state-of-the-art performance for NER tasks in Shona.
- Hybrid methods. Combining rule-based and machine learning approaches, hybrid methods enhance NER effectiveness by leveraging the strengths of both techniques.
