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Related Questions
- How do word embeddings handle the problem of polysemy in natural language processing?
- Can you explain how word embeddings capture nuances of word meanings for words with multiple senses?
- What are the common techniques used to address the issue of homograph detection in NLP using word embeddings?
- How do word embeddings account for the context-dependent nature of word meanings?
- Can you describe the role of embeddings in mitigating the effects of polysemy and homograph in machine learning models?
- What are some of the challenges associated with using word embeddings to address polysemy and homograph in NLP tasks?
- How do word embeddings help to reduce the impact of ambiguity in word meanings on NLP model performance?
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