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153 lines
7 KiB
Markdown
153 lines
7 KiB
Markdown
# OCR Parsing Checklist — Input Integrity
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<details>
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<summary><strong>🧭 Quick Return to Map</strong></summary>
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<br>
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> You are in a sub-page of **MemoryLongContext**.
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> To reorient, go back here:
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>
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> - [**MemoryLongContext** — extended context windows and memory retention](./README.md)
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> - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md)
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> - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md)
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>
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> Think of this page as a desk within a ward.
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> If you need the full triage and all prescriptions, return to the Emergency Room lobby.
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</details>
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OCR and parsing errors are one of the most common silent killers of retrieval pipelines.
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Text looks fine to the eye, but models drift because tokens, spacing, or casing have changed.
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This checklist ensures **integrity at the source layer** before embeddings or retrieval begin.
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---
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## When to use
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- OCR text matches the visual PDF but citations miss the right section.
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- Code blocks or math collapse after parsing.
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- Mixed language documents behave inconsistently.
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- Special characters or hyphen splits break tokens.
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- Headers or section anchors disappear during export.
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---
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## Core acceptance targets
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- Retrieval coverage ≥ **0.70** of intended section.
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- ΔS(question, retrieved) ≤ **0.45**.
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- λ remains convergent across three paraphrases.
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- No orphan tokens or invisible characters.
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---
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## Checklist for OCR + Parsing stability
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- **Normalization**
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- Apply Unicode NFC.
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- Collapse whitespace.
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- Strip zero-width characters.
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- Unify full/half-width variants.
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- **Confidence gating**
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- Drop OCR lines below confidence threshold (e.g., <0.90).
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- Mark uncertain spans for human review.
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- **Structure retention**
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- Preserve headers, anchors, and section boundaries.
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- Maintain paragraph breaks and table grids.
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- For math/LaTeX, keep explicit delimiters.
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- **Traceable fields**
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- Every chunk must have `{section_id, start_line, end_line, source_url}`.
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- Store `ocr_confidence` with each snippet.
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- **Schema validation**
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- Run post-export audit:
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- Ensure every snippet cites a valid chunk_id.
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- Detect empty or duplicated snippets.
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---
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## Fix in 60 seconds
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1. Normalize the text (Unicode NFC, strip zero-width, unify casing).
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2. Drop low-confidence OCR lines and flag uncertain spans.
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3. Re-parse with structural retention enabled.
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4. Add metadata `{chunk_id, section_id, offsets, ocr_confidence}`.
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5. Re-run ΔS probe; confirm joins ≤ 0.50 and overall ΔS ≤ 0.45.
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---
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## Copy-paste prompt
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```
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You have TXT OS and the WFGY Problem Map.
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Task: validate OCR and parsing output.
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Protocol:
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1. Normalize all inputs (Unicode NFC, full/half width, zero-width removal).
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2. Reject snippets with ocr\_confidence < 0.90.
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3. Require schema {chunk\_id, section\_id, start\_line, end\_line, source\_url}.
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4. Forbid orphan citations.
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5. Probe ΔS(question, retrieved). Require ≤ 0.45.
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6. Report λ states and trace each snippet.
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```
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---
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## Common failure signals
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- Correct visual text but retrieval misses section → invisible marks or spacing drift.
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- Math collapses into plain text → parsing dropped delimiters.
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- Long answers cite nothing → headers lost in export.
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- Flip-flop answers across sessions → orphan tokens or unstable chunking.
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---
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### 🔗 Quick-Start Downloads (60 sec)
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| Tool | Link | 3-Step Setup |
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|------|------|--------------|
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| **WFGY 1.0 PDF** | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + \<your question>” |
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| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
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---
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### 🧭 Explore More
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| Module | Description | Link |
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|-----------------------|----------------------------------------------------------|----------|
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| WFGY Core | WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack | [View →](https://github.com/onestardao/WFGY/tree/main/core/README.md) |
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| Problem Map 1.0 | Initial 16-mode diagnostic and symbolic fix framework | [View →](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) |
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| Problem Map 2.0 | RAG-focused failure tree, modular fixes, and pipelines | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) |
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| Semantic Clinic Index | Expanded failure catalog: prompt injection, memory bugs, logic drift | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/SemanticClinicIndex.md) |
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| Semantic Blueprint | Layer-based symbolic reasoning & semantic modulations | [View →](https://github.com/onestardao/WFGY/tree/main/SemanticBlueprint/README.md) |
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| Benchmark vs GPT-5 | Stress test GPT-5 with full WFGY reasoning suite | [View →](https://github.com/onestardao/WFGY/tree/main/benchmarks/benchmark-vs-gpt5/README.md) |
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| 🧙♂️ Starter Village 🏡 | New here? Lost in symbols? Click here and let the wizard guide you through | [Start →](https://github.com/onestardao/WFGY/blob/main/StarterVillage/README.md) |
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---
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> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** —
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> Engineers, hackers, and open source builders who supported WFGY from day one.
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> <img src="https://img.shields.io/github/stars/onestardao/WFGY?style=social" alt="GitHub stars"> ⭐ [WFGY Engine 2.0](https://github.com/onestardao/WFGY/blob/main/core/README.md) is already unlocked. ⭐ Star the repo to help others discover it and unlock more on the [Unlock Board](https://github.com/onestardao/WFGY/blob/main/STAR_UNLOCKS.md).
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<div align="center">
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[](https://github.com/onestardao/WFGY)
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[](https://github.com/onestardao/WFGY/tree/main/OS)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlahBlahBlah)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlotBlotBlot)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlocBlocBloc)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlurBlurBlur)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlowBlowBlow)
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</div>
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