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Reframing a Research Query
A medical researcher is using a large language model to analyze clinical trial notes. Their initial prompt is: 'Tell me about the relationship between Drug X and patient side effects.' This prompt is too broad to yield specific, useful results. Rewrite this task as two distinct, more effective prompts that frame the problem in a question-answering format. One prompt should solicit an open-ended answer, and the other should solicit a more constrained, specific answer (e.g., a yes/no or categorical response).
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Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Application in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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MMLU Benchmark
A product development team is using a large language model to check if a new product concept aligns with their company's core principles. Their initial prompt, "Analyze if our new 'Smart-Mug' concept is consistent with our principles of 'sustainability,' 'simplicity,' and 'affordability'," yields vague and unhelpful responses. How could this reasoning task be most effectively restructured into a question-answering format to guide the model toward a more structured and deductive output?
Improving a Data Analysis Prompt
Reframing a Research Query