This is a learning outline. A complete worked tutorial has not been published for this topic yet.
01
Define target fields
Define mandatory fields for a sample invoice
Evidence: t016/m01/evidence
02
Extract with source pointers
Extract values while preserving source-page references
Evidence: t016/m02/evidence
03
Validate uncertain values
Reject a missing date and reconcile line-item totals
Evidence: t016/m03/evidence
04
Review exceptions
Send uncertain values to manual review
Evidence: t016/m04/evidence
03 / TRY IT
Apply the micro-course
Demonstrate the promised artifact
Send uncertain values to manual review
Independently explain and change one assumption in a checked structured-record set.
Keep your work
Flag ambiguous values rather than inventing data and preserve source provenance.; The documented failure/uncertainty is visible, and no prohibited action or unsupported success claim occurs.; The learner predicts and verifies the change; AI output is not accepted without understanding.
Check your understanding
Flag ambiguous values rather than inventing data and preserve source provenance.
Show one small example, the expected result and the reasoning behind it.
Record one limitation or edge case and a question to discuss with a mentor.
04 / LEARN WITH HELP
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