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Related Questions
- Can subword models capture the nuances of word meanings, such as homophones, or do they rely on context to disambiguate?
- How do subword models handle homophones with different grammatical functions, such as 'bank' (financial institution) and 'bank' (riverbank)?
- Can subword models learn to distinguish between homophones with similar but distinct meanings, such as 'flower' (the plant) and 'flower' (to decorate with flowers)?
- Do subword models have difficulty with homophones that are pronounced the same but have different spellings, such as 'to', 'too', and 'two'?
- Can subword models be fine-tuned to improve their performance on homophone pairs with different meanings?
- How do subword models compare to other NLP models, such as character-level models, in their ability to represent and distinguish between homophones?
- Can subword models be used to generate text that accurately represents the nuances of homophones, such as in poetry or literary works?
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