Hybrid methods combine different techniques and approaches to improve performance in tasks like information extraction and named entity recognition. By integrating rule-based systems with machine learning algorithms, these methods leverage the strengths of both approaches, often resulting in enhanced accuracy and adaptability when processing natural language data.
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