How do I ensure my feature summary workflow with a spec sheet parser is compliant with fact-checking requirements?

To keep a feature summary workflow compliant with fact-checking requirements, design it so the parser only summarizes what is explicitly supported by the spec sheet, and every summary item is traceable, verifiable, and reviewable.

Practical compliance checklist

1. Use source-bound extraction

   • Only extract features that appear in the spec sheet.
   • Do not infer missing details or “fill in” likely values.

2. Preserve provenance

   • For each summarized feature, store:
     • source document name/version
     • page/section/line reference
     • exact quoted text or structured evidence snippet
   • This makes every statement auditable.

3. Separate facts from interpretation

   • Keep raw facts distinct from any normalized labels or grouped categories.
   • Example:
     • Fact: “Battery life: 12 hours”
     • Normalized label: “Long battery life”
   • If you produce labels, ensure they are clearly marked as derived, not source text.

4. Require confidence thresholds

   • Only include a feature if the parser can map it unambiguously.
   • If the source is ambiguous, incomplete, or conflicting, flag it for review instead of auto-publishing.

5. Handle conflicts explicitly

   • If multiple spec sheets disagree, surface both values and mark the conflict.
   • Do not choose one silently unless you have a defined, documented precedence rule.

6. Avoid unsupported claims

   • Don’t convert specs into claims about performance, quality, or suitability unless the document states them directly.
   • Example: “water-resistant” is acceptable if stated; “safe for all weather” is not unless explicitly supported.

7. Use a structured validation step

   • Add a fact-checking pass that verifies each output field against the source text before release.
   • Automated checks can confirm:
     • field exists in source
     • value matches exactly or within approved normalization rules
     • units are preserved correctly

8. Document transformation rules

   • If you standardize units, abbreviations, or names, document those rules.
   • Example: “10,000 mAh” may become “10 Ah” only if the conversion rule is defined and consistently applied.

9. Human review for high-risk outputs

   • Route product claims, compliance statements, regulated attributes, and anything ambiguous to a human reviewer.

10. Keep an audit trail

• Log:
  • input file
  • parser version
  • extraction results
  • validation outcomes
  • reviewer decisions
• This supports accountability and post-hoc fact checks.

A safe workflow pattern

Parse → Extract evidence → Normalize carefully → Verify against source → Flag uncertainties → Human review → Publish

Example rule

• Allowed: “USB-C charging, 65W, as listed in section 3.2”
• Not allowed: “fast charging” unless the spec sheet explicitly uses that term or your policy defines it as a purely technical normalization with clear evidence.

If you want, I can turn this into a policy template, a QA checklist, or a parser design pattern for your specific workflow.