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Related Questions
- What are the common techniques used in NLP pipelines for contextual disambiguation?
- How do NLP models handle out-of-vocabulary words, and what are the implications for contextual disambiguation?
- Can you explain the role of word embeddings in resolving contextual ambiguity in NLP pipelines?
- What are the differences between supervised and unsupervised approaches to contextual disambiguation in NLP?
- How do contextualized embeddings, such as those used in BERT, improve disambiguation of unfamiliar words or phrases?
- What are the challenges of integrating domain-specific knowledge into NLP pipelines to improve contextual disambiguation?
- Can you discuss the trade-offs between accuracy and computational efficiency in contextual disambiguation algorithms?
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