How does Hebrew Named Entity Recognition work?
- Rule-based methods. These methods use a set of predefined linguistic rules to identify entities based on patterns and keywords found in the text.
- Machine Learning models. These models are trained on annotated Hebrew text data to recognize entities using statistical methods and can adapt to new contexts.
- Deep Learning approaches. Deep learning models, such as neural networks, analyze large datasets of Hebrew text to learn complex representations of entities with high accuracy.
- Hybrid methods. Hybrid methods combine rule-based techniques and machine learning to leverage the strengths of both approaches for improved accuracy.
