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Related Questions
- How do context and semantic meaning interact in polysemous words, and what implications does this have for natural language processing?
- Can you explain how machine learning models, such as word embeddings, represent the relationship between context and semantic meaning in polysemous words?
- In what ways do polysemous words challenge traditional notions of meaning, and how do machine learning models address these challenges?
- How do contextual cues, such as syntax and pragmatics, influence the semantic meaning of polysemous words in machine learning models?
- What role do polysemous words play in language acquisition and learning, and how do machine learning models capture this complexity?
- Can you discuss the limitations of current machine learning approaches to representing the relationship between context and semantic meaning in polysemous words?
- How do machine learning models handle the ambiguity of polysemous words in different linguistic and cultural contexts?
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