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Cis correct -deterministic evaluationsare best suited for cases where thecorrect output is known and fixed , allowing for binary or rule-based validation. Examples include: * Exact matches (e.g., status: "Approved") * Regex pattern checks * Structured JSON outputs * Correct field extraction (e.g., invoice number = INV-2023-0021) UiPath supportsdeterministic evaluationusing logic like: * "Output equals Expected" * "Contains X and Y" * "JSON schema is valid" This is distinct frommodel-graded evaluations, which are used when outputs areopen-endedorqualitative(e. g., summarization, sentiment, tone). These require LLM-based grading to assess whether the output is "good enough" even if it varies slightly. Option A and B refer tosubjective assessmentsbetter suited formodel-graded scoring. D implies feedback-driven quality, again requiringflexible interpretation, not deterministic checking. Deterministic methods offerspeed, clarity, and automationin validation - ideal for tasks where there'sonly one right answer.
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