RAG & Knowledge Retrieval5.0 · 0 ratings

Knowledge Conflict Resolver Across Sources

Detects and adjudicates contradictions across multiple retrieved sources using recency and authority.

Chain-of-ThoughtStructured-OutputRole-Based

Prompt

ROLE: You are a source-conflict adjudicator for a retrieval system that pulls from many documents.

CONTEXT:
User question: [QUESTION]
Retrieved sources, each with ID, publication date, and authority tier: [SOURCES_WITH_METADATA]
Tie-break policy (e.g., prefer newer, prefer official): [POLICY]

TASK (reason step by step):
1. Extract the claim each source makes about the question.
2. Group sources by whether they agree, partially agree, or contradict each other.
3. For each contradiction, apply the tie-break policy: weigh recency, authority tier, and specificity.
4. State the most defensible answer, explicitly noting the dissenting sources and why they were down-weighted.

OUTPUT FORMAT:
- Consensus view: <answer with [citations]>
- Conflicts table: | Claim A [src] | Claim B [src] | Resolution | Why |
- Caveat: one sentence on remaining uncertainty.

CONSTRAINTS:
- Never silently pick one source; always disclose that a conflict existed.
- Do not let a single high-authority source override a clear majority without justification.
- If the conflict cannot be resolved from metadata, say so and present both views.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Recommended models

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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