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arXiv · 2509.24212

ScenarioBench: Trace-Grounded Compliance Evaluation for Text-to-SQL and RAG

Zahra Atf·Peter R Lewis
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Abstract

ScenarioBench is a policy-grounded, trace-aware benchmark for evaluating Text-to-SQL and retrieval-augmented generation in compliance contexts. Each YAML scenario includes a no-peek gold-standard package with the expected decision, a minimal witness trace, the governing clause set, and the canonical SQL, enabling end-to-end scoring of both what a system decides and why. Systems must justify outputs using clause IDs from the same policy canon, making explanations falsifiable and audit-ready. The evaluator reports decision accuracy, trace quality (completeness, correctness, order), retrieval effectiveness, SQL correctness via result-set equivalence, policy coverage, latency, and an explanation-hallucination rate. A normalized Scenario Difficulty Index (SDI) and a budgeted variant (SDI-R) aggregate results while accounting for retrieval difficulty and time. Compared with prior Text-to-SQL or KILT/RAG benchmarks, ScenarioBench ties each decision to clause-level evidence under strict grounding and no-peek rules, shifting gains toward justification quality under explicit time budgets.

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Zahra Atf, Peter R Lewis. 2025-09-29. ScenarioBench: Trace-Grounded Compliance Evaluation for Text-to-SQL and RAG. https://arxiv.org/abs/2509.24212

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