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Related Questions
- How do word embeddings handle out-of-vocabulary words in entity recognition models?
- What are the limitations of using subword models in entity recognition?
- Can you explain the concept of 'unk' token in entity recognition models and how it handles out-of-vocabulary words?
- How do neural network-based entity recognition models handle out-of-vocabulary words compared to traditional machine learning models?
- What are the challenges of handling out-of-vocabulary words in entity recognition models for low-resource languages?
- How do pre-trained language models help in handling out-of-vocabulary words in entity recognition tasks?
- What are the trade-offs between using pre-trained word embeddings and fine-tuning them for out-of-vocabulary words in entity recognition models?
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