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A financial institution is using Azure OpenAI Service to generate market commentary based on real-time financial data. The generated commentary needs to be precise, factual, and directly supported by the provided data, avoiding any speculative or overly creative language. The AI engineer is designing the prompt. Which characteristic of an effective prompt for this scenario is most critical?
- AFocusing on brevity and data-driven instructions.
- BIncluding diverse stylistic examples for varied output.
- CAllowing for open-ended interpretations of the data.
- DEmphasizing creativity and imaginative language.
Show answer & explanationAnswer & explanation
Correct answer: A. Focusing on brevity and data-driven instructions.
For financial commentary requiring precision and factual accuracy directly from data, prompts must be concise and data-driven. This means providing clear instructions to stick to the facts and explicitly incorporating the relevant data, guiding the model to generate objective, non-speculative content.
Why the other options are wrong
- B. Diverse stylistic examples would encourage varied output, which is contrary to the need for precise, factual commentary.
- C. Open-ended interpretations would lead to speculation, which is undesired.
- D. Creativity and imaginative language are explicitly what should be avoided in this scenario.
Concise & Data-Driven Prompting
A prompt engineering technique that instructs the LLM to generate responses strictly based on provided data, using clear, brief language, to ensure factual accuracy and avoid speculation.
- Essential for applications requiring high factual accuracy (e.g., finance, legal).
- Minimizes hallucinations and speculative content.
- Involves clear instructions and direct integration of relevant data.
Memory trick: For facts, prompt briefly, with data, and nothing extra.