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Related Questions
- How can we employ subword tokenization to handle out-of-vocabulary entities?
- What are some techniques for augmenting the training data to improve a model's ability to recognize out-of-vocabulary entities?
- Can you explain the concept of character-level modeling and its potential benefits in handling out-of-vocabulary entities?
- What are the trade-offs between using character-level and subword-level modeling for out-of-vocabulary entity recognition?
- How can we leverage external knowledge graphs or dictionaries to improve a model's performance on out-of-vocabulary entities?
- What is the role of pre-training and fine-tuning in improving a model's robustness to out-of-vocabulary entities?
- Can you discuss the impact of model size and complexity on the ability to handle out-of-vocabulary entities?
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