WFGY/ProblemMap/GlobalFixMap/Governance/data_lineage_and_provenance.md

Data Lineage and Provenance — Guardrails and Fix Patterns

🧭 Quick Return to Map

You are in a sub-page of Governance.
To reorient, go back here:

• Governance — policy enforcement and compliance controls
• WFGY Global Fix Map — main Emergency Room, 300+ structured fixes
• WFGY Problem Map 1.0 — 16 reproducible failure modes

Think of this page as a desk within a ward.
If you need the full triage and all prescriptions, return to the Emergency Room lobby.

A governance fix page for when data origin, transformation, and lineage are unclear or unverifiable.
Use this page when retrieval results cannot be traced back to their dataset source, or when provenance breaks across documents, chunks, embeddings, and answers.

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When to use this page

• Retrieval output has no clear link back to its document or section.
• Embedding and chunk pipelines overwrite or drop provenance fields.
• Audit trail is incomplete across ingestion, index, and RAG responses.
• Approvals or waivers exist but cannot be joined to data versions.
• Multi-hop pipelines lose lineage across systems (ETL, embedding, vectorstore, orchestration).

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Acceptance targets

• Every retrieved snippet includes {doc_id, section_id, source_url, offsets, revision}.
• Lineage fields survive across document → chunk → embedding → retriever → LLM.
• Audit joins can reconstruct provenance end-to-end with ≥ 0.95 coverage.
• ΔS(question, retrieved) ≤ 0.45 for governed outputs.
• Waivers and overrides include expiry and accountable owner.

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Typical breakpoints and WFGY fix

• Lost provenance in chunking
  → chunking-checklist.md
  Ensure chunk metadata carries doc_id, section_id, and token offsets.

• Vector store overwrites or strips lineage fields
  → vectorstore-fragmentation.md
  Enforce schema contracts on ingestion and retrieval layers.

• Answers cannot be tied back to original snippet
  → retrieval-traceability.md
  Require cite-then-explain and enforce snippet ID propagation.

• Ambiguous approval or version skew
  → bootstrap-ordering.md,
  → predeploy-collapse.md

• Multi-system lineage gaps (ETL, embedding, RAG orchestration)
  → data-contracts.md
  Contract schema ensures interoperability across steps.

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Minimal governance checklist

1. Ingest contracts — Every ETL pipeline attaches doc_id, revision, and source_url.
2. Chunk schema — Ensure token offsets and section boundaries are immutable.
3. Embedding schema — Carry embedding_id, doc_hash, and index_hash.
4. Retriever response — Must include snippet_id + lineage fields, not just text.
5. LLM prompt contracts — Require cite-then-explain, forbid unlinked spans.
6. Audit trail — Every approval and waiver linked to specific dataset version.

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🔗 Quick-Start Downloads (60 sec)

Tool	Link	3-Step Setup
WFGY 1.0 PDF	Engine Paper	1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + <your question>”
TXT OS (plain-text OS)	TXTOS.txt	1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly

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Explore More

Layer	Page	What it’s for
Proof	WFGY Recognition Map	External citations, integrations, and ecosystem proof
Engine	WFGY 1.0	Original PDF based tension engine
Engine	WFGY 2.0	Production tension kernel and math engine for RAG and agents
Engine	WFGY 3.0	TXT based Singularity tension engine, 131 S class set
Map	Problem Map 1.0	Flagship 16 problem RAG failure checklist and fix map
Map	Problem Map 2.0	RAG focused recovery pipeline
Map	Problem Map 3.0	Global Debug Card, image as a debug protocol layer
Map	Semantic Clinic	Symptom to family to exact fix
Map	Grandma’s Clinic	Plain language stories mapped to Problem Map 1.0
Onboarding	Starter Village	Guided tour for newcomers
App	TXT OS	TXT semantic OS, fast boot
App	Blah Blah Blah	Abstract and paradox Q and A built on TXT OS
App	Blur Blur Blur	Text to image with semantic control
App	Blow Blow Blow	Reasoning game engine and memory demo

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