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Related Questions
- What are the effects of subword tokenization on named entity recognition (NER) performance?
- How do different tokenization strategies impact the recall of NER models, especially for out-of-vocabulary words?
- Can you explain the impact of wordpiece tokenization on the precision of NER models for entities with hyphenated names?
- What are the implications of using character-based tokenization on the overall F1-score of an NER model?
- How do the choices of tokenization strategy influence the ability of NER models to recognize entities in languages with complex scripts?
- What are some strategies for mitigating the negative effects of tokenization on NER performance in cases where the input data contains a lot of variation in formatting and punctuation?
- Can you describe a scenario where a different tokenization strategy would significantly improve the performance of a given NER model?
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