Observability & Evaluation · Software component
Reasoning Chain Validator
Software componentObservability & EvaluationObservability & Evaluationarc:ReasoningChainValidator
An evaluation component that reconstructs an agent's intermediate multi-hop reasoning steps and validates each against annotated supporting facts or knowledge-graph triples, scoring answers jointly with evidence.
Responsibility. Checks faithfulness of intermediate reasoning and supporting evidence.
Also known as: Supporting fact evaluation, Joint EM/F1 scoring, Reasoning chain evaluation
Relationships
is invoked by dependency
reads dependency
evaluates assurance
Design guidance
- MUST report joint metrics as primary, not secondary, where transparency or audits matter.
- SHOULD measure success at each hop independently to reveal early-hop breakdowns.
Quantitative guidance
As stated by the sources; verify before use.
- HotpotQA distractor: answer EM 44-45%, F1 58-59%; supporting-fact EM 22%; joint EM/F1 11-12% / 40-41% (Ch3.3).
- HotpotQA full wiki: answer F1 34%; joint 2.6% EM / 17.8% F1 (Ch3.3).
- For N-hop questions there are 2^(N+1) possible reasoning chains (Ch3.3).
Classification
- Patterns
- Sub-question answering evaluationJoint answer-plus-supporting-fact metricsHop-level success stratification
- Technologies
- HotpotQA2WikiMultiHopQAMuSiQue
- Quality attributes
- Explainability (NIST AI RMF: explainable and interpretable)Transparency and accountability (NIST AI RMF: accountable and transparent)
- Risks mitigated
- Hallucinated intermediate stepsCorrect answers via shortcuts or dataset artifacts
Sources
- Ch3.3: T. Nguyen, "Web Navigation and Interaction Benchmarks," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 3.3. ISBN: 9798244538229.