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Related Questions
- What are the common pitfalls in named entity recognition for large language models?
- How do handling out-of-vocabulary words, typos, and abbreviations affect entity identification in text data?
- What role does contextual understanding play in accurately identifying entities in text data for large language models?
- Can you explain the challenges of entity disambiguation in text data, particularly when entities have multiple meanings or context-dependent interpretations?
- How do large language models handle entity recognition in cases where entities are mentioned in a non-standard or unconventional manner?
- What are some common biases that can affect entity identification in text data, and how can they be mitigated in large language models?
- Can you discuss the impact of entity granularity on the accuracy of entity identification in text data for large language models?
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