Context Management & Reliability/Reliability & Provenance
Intermediate8 min

Information Provenance & Uncertainty

Tracking where information comes from in multi-agent research systems. Claim-source mappings, handling conflicting statistics across credible sources, temporal data attribution, and rendering content types appropriately.

Quick Reference

  • →Source attribution is lost during summarization unless you maintain explicit claim-source mappings
  • →Conflicting statistics from credible sources should be annotated with both values and sources, not arbitrarily resolved
  • →Require publication dates on all sources to prevent temporal differences from being misinterpreted as contradictions
  • →Each claim in the final output should trace back to a specific source, URL, excerpt, and date
  • →Financial data should render as tables with precise figures; narrative content should render as prose
  • →A claim supported by 3 independent sources is stronger than one supported by 1 -- track support count
  • →Distinguish between well-established findings (multiple sources agree) and contested findings (sources disagree)
  • →Don't arbitrarily select one value when credible sources conflict -- present both with attribution
  • →Temporal context explains many apparent contradictions: 2023 data and 2025 data aren't 'conflicting', they're from different time periods
  • →The final report should make its confidence basis transparent: 'Based on 4 of 5 planned sources, with Source X unavailable'

Why Information Provenance Matters

In multi-agent research systems (Scenario 3), subagents gather information from multiple sources. The coordinator synthesizes these findings into a coherent report. The critical question is: can the user trace any claim in the final report back to its original source? Without provenance, the report is an unsourced assertion. With provenance, it's a verifiable research product.

Exam context

Scenario 3 (Multi-Agent Research) is the primary testing ground for provenance. Questions will ask how a coordinator should handle conflicting data from subagents, how to present uncertain findings, and how to maintain source attribution through summarization.

Provenance failures manifest in three ways: (1) source loss -- claims appear in the final report with no attribution, (2) false consensus -- multiple claims from the same source appear to be independent verification, and (3) temporal confusion -- data from different years is treated as conflicting rather than sequential. Each failure undermines the report's reliability.