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Related Questions
- What are the key techniques used by large language models to identify and extract entities from unstructured text?
- How do large language models utilize natural language processing (NLP) to recognize and extract relevant entities from text data?
- Can you explain the role of named entity recognition (NER) in text summarization and how large language models implement it?
- What is the significance of entity extraction in text summarization, and how do large language models improve it?
- How do large language models handle ambiguity and uncertainty in entity recognition, and what techniques do they employ to mitigate these issues?
- What are the challenges associated with entity recognition in text summarization, and how do large language models address them?
- Can you discuss the impact of pre-training and fine-tuning on the performance of large language models in entity recognition and extraction?
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