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Related Questions
- What is the difference between contextualized embeddings and non-contextualized embeddings in NER tasks?
- How do contextualized embeddings capture nuances in natural language, such as word order and context?
- Can you provide an example of how contextualized embeddings improve NER task performance compared to non-contextualized embeddings?
- How do contextualized embeddings handle out-of-vocabulary words in NER tasks?
- What is the role of contextualized embeddings in capturing entity relationships and nuances in NER tasks?
- Can contextualized embeddings be fine-tuned for specific NER tasks, such as entity recognition in specific domains?
- How do contextualized embeddings compare to other NER techniques, such as rule-based methods and machine learning models?
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