CCA-F: Claude Certified Architect — Foundations

By Anthropic · Question Mode

QuestionQ101

Context Management & Reliability

You are developing a structured data-extraction system using Claude. The system pulls information from unstructured documents, validates outputs with JavaScript Object Notation (JSON) schemas, and preserves high accuracy. It must gracefully handle edge cases and integrate with downstream systems.

Your extraction pipeline validates outputs against JSON schemas, but limited reviewer capacity means human reviewers can handle approximately 5% of the total extraction volume.

What is the most effective basis for choosing which extractions to send for human review?

Explanation

Human review is most valuable when directed to records with the highest estimated risk of an incorrect extraction. Low model confidence and source documents that are ambiguous or contradictory are direct indicators of uncertainty, so routing those items concentrates limited review capacity on cases where it can most improve accuracy and safely resolve edge cases.

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