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Related Questions
- How do large language models handle homographs and context-dependent word meanings?
- What techniques are used to disambiguate words with multiple meanings in real-world applications?
- Can large language models leverage external knowledge graphs or databases to improve word sense resolution?
- How do contextual clues such as syntax and semantics influence large language models' ability to resolve word sense ambiguity?
- What role do neural networks play in resolving word sense ambiguity in large language models?
- How do large language models handle polysemous words and their nuances in context?
- Are there any real-world case studies or examples of large language models successfully resolving word sense ambiguity in practical applications?
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