S6 · scenario91 questions · 21 free
Structured data extraction (S6)
Extract from unstructured docs, validate with JSON schema, handle edge cases.
The Structured Data Extraction scenario (S6) is pulling clean, validated data out of messy documents: schema-enforced output, validation, and the edge cases that break naive extractors. The exam tests precision and recovery, not just a lucky parse.
Expect questions on enforcing structured output with JSON schemas, designing prompts with explicit criteria to reduce false positives, building validation, retry, and feedback loops, and batching extraction efficiently at volume.
This scenario spans 12 subtopic areas, covered by 91 practice questions across 25 easy, 43 medium, and 23 hard items.
Sample question · free
Your extraction system processes invoices with varying layouts. After adding few-shot examples to the prompt, validation against the JSON schema shows fewer missing fields. What does this improvement demonstrate?
What's covered
Subtopic areas in Structured data extraction, drawn from the exam blueprint:
4.1Design prompts with explicit criteria to improve precision and reduce false positives124.2Apply few-shot prompting to improve output consistency and quality114.3Enforce structured output using tool use and JSON schemas114.4Implement validation, retry, and feedback loops for extraction quality94.5Design efficient batch processing strategies114.6Design multi-instance and multi-pass review architectures105.1Manage conversation context to preserve critical information across long interactions45.2Design effective escalation and ambiguity resolution patterns55.3Implement error propagation strategies across multi-agent systems55.4Manage context effectively in large codebase exploration45.5Design human review workflows and confidence calibration35.6Preserve information provenance and handle uncertainty in multi-source synthesis6