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How can I improve entity recognition in Rasa?
Asked on Nov 05, 2025
Answer
Improving entity recognition in Rasa involves refining your training data and utilizing Rasa's built-in features to enhance model performance. You can achieve better entity recognition by providing diverse examples and leveraging Rasa's entity extraction components like Duckling or custom components.
Example Concept: To improve entity recognition in Rasa, ensure your training data includes varied examples of entity usage across different intents. Use Rasa's NLU pipeline to configure entity extractors like CRFEntityExtractor or DIETClassifier, and consider integrating Duckling for recognizing dates, times, and numbers. Regularly evaluate and update your training data based on model performance and real user interactions.
Additional Comment:
- Review and expand your NLU training data with diverse entity examples.
- Configure the NLU pipeline to include appropriate entity extractors.
- Test the model with real-world data and adjust based on performance metrics.
- Consider using pre-trained models or external tools like Duckling for specific entity types.
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