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Related Questions
- How do entity-based attention models capture contextual information to resolve polysemy in language?
- Can you explain the role of word embeddings in entity-based attention models for disambiguating word senses?
- What are some common techniques used in entity-based attention models to handle homographs and homophones?
- How do entity-based attention models handle multiple possible interpretations of a word in a sentence?
- In what ways do entity-based attention models use contextual information to disambiguate word meanings?
- Can you provide an example of how entity-based attention models might disambiguate between different meanings of a word in a sentence?
- What are some challenges in using entity-based attention models for disambiguating word meanings, and how are they addressed?
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