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Related Questions
- What are the common challenges faced by machine learning models in entity recognition tasks when encountering unseen words?
- How do unseen words affect the performance of named entity recognition (NER) models in real-world applications?
- Can you explain the concept of out-of-vocabulary (OOV) words and their impact on machine learning models in entity recognition tasks?
- What techniques can be employed to handle unseen words in entity recognition tasks, such as using subword models or word embeddings?
- How does the presence of unseen words influence the accuracy and robustness of machine learning models in entity recognition tasks?
- What role does data augmentation play in mitigating the impact of unseen words on machine learning models in entity recognition tasks?
- Can you discuss the trade-offs between model complexity and the ability to handle unseen words in entity recognition tasks?
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