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Related Questions
- How do contextualized embeddings address the issue of polysemy and homograph ambiguity in NER tasks?
- Can you provide an example of a use case where contextualized embeddings outperformed traditional word embeddings in a named entity recognition task?
- What is the impact of contextualized embeddings on the performance of NER models in low-resource languages?
- How do contextualized embeddings handle out-of-vocabulary words in NER tasks?
- What is the difference in computational cost between training contextualized embeddings and traditional word embeddings?
- Can contextualized embeddings learn to capture domain-specific knowledge and nuances in NER tasks?
- How do contextualized embeddings compare to traditional word embeddings in terms of interpretability and explainability in NER tasks?
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