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Related Questions
- How does named entity recognition (NER) aid large language models (LLMs) in distinguishing between homographs with different meanings?
- Can you explain the role of NER in resolving ambiguity in LLMs when encountering homographs?
- How does NER help LLMs identify the correct meaning of a homograph in a given context?
- In what ways can NER help LLMs improve their ability to understand homographs with multiple senses?
- Can you provide examples of how NER can be used to disambiguate homographs in LLMs?
- How does NER contribute to the overall performance of LLMs in handling homographs?
- What are the benefits of using NER in conjunction with other NLP techniques to address homograph identification in LLMs?
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