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Related Questions
- What are some common cognitive biases that prompt engineers should be aware of when designing prompts for language models?
- How can prompt engineers use linguistic principles such as semantics and pragmatics to create more effective and explainable prompts?
- What are some strategies for designing prompts that minimize the risk of linguistic ambiguity and ensure clear output from language models?
- Can you provide examples of well-designed prompts that utilize cognitive biases and linguistics principles to promote clear and explainable output?
- How can prompt engineers use active voice and clear subject-verb-object structure to improve the clarity of their prompts?
- What role do ontologies and knowledge graphs play in designing prompts that promote clear and explainable output?
- How can prompt engineers use rhetorical devices such as metaphors and analogies to make their prompts more engaging and effective?
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