To handle contradictory information in retrieved documents, the prompt should explicitly instruct the model to recognize discrepancies, evaluate sources, and explain its reasoning. The prompt must outline a structured approach to resolve conflicts, such as prioritizing source credibility, recency, or consensus among documents. For example, the prompt could direct the model to first identify conflicting claims, then compare factors like publication date, author expertise, or the number of sources supporting each claim. Finally, the model should present a conclusion that either resolves the conflict or transparently acknowledges unresolved disagreements, ensuring users understand the limitations of the information.
A practical example involves historical events with conflicting dates. The prompt might instruct the model to flag the discrepancy, check if one date is supported by authoritative sources (e.g., peer-reviewed journals), or determine if newer research contradicts older claims. In medical contexts, conflicting treatment recommendations could be resolved by prioritizing recent clinical guidelines over outdated studies. The prompt could also require the model to avoid speculation—if no clear resolution exists, it should summarize both perspectives and highlight the uncertainty. For instance, if two credible sources disagree on a software framework’s best practices, the model might explain the trade-offs of each approach instead of favoring one arbitrarily.
The prompt should also enforce transparency. For example, it could require the model to explicitly state, “Documents A and B conflict on [issue]. Document A (published in 2023) states X, while Document B (a 2010 whitepaper) states Y. Based on recency and peer-reviewed status, X is likely more reliable, though Y may apply in legacy systems.” This approach ensures users receive a balanced view while understanding the rationale behind the model’s conclusion. By structuring the prompt to mandate source evaluation, conflict acknowledgment, and clear reasoning, developers can mitigate the risks of presenting conflicting information as definitive.