ABBYY OCR (FineReader / FlexiCapture): Guardrails and Fix Patterns

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DocumentAI_OCR — document parsing and optical character recognition

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.

Use this page when ABBYY OCR powers ingestion of scanned PDFs, complex layouts, forms, or multilingual documents.
ABBYY is enterprise-grade, but still prone to schema drift, field misalignment, and unstable table anchors.

Open these first

Visual map and recovery: RAG Architecture & Recovery
Retrieval knobs: Retrieval Playbook
Citation schema: Retrieval Traceability
Schema stability: Data Contracts
Embedding vs meaning: Embedding ≠ Semantic
Hallucination and entropy drift: Hallucination, Entropy Collapse
Chunk boundaries: Chunking Checklist

Core acceptance

ΔS(question, retrieved) ≤ 0.45
Coverage ≥ 0.70 across fields and tokens
λ convergent on three paraphrases and two seeds
Form fields ≥ 95% aligned with schema contract

Typical breakpoints → structural fix

Form fields drift across runs (invoice totals, line items misaligned)
→ Data Contracts, Retrieval Traceability
Table anchors collapse (multi-column invoices, receipts)
→ Chunking Checklist, clamp with BBMC
Handwriting extraction unstable
→ Entropy Collapse
Injected payload in OCR notes layer
→ Prompt Injection
Multilingual contract fields mismatched
→ Embedding ≠ Semantic

Fix in 60 seconds

Enforce field schema: require field_id, bbox, confidence, revision_id.
Compute ΔS on critical fields (e.g. total_amount, invoice_date).
Apply λ probes with different template libraries.
Clamp instability with BBAM and log coverage.
Rebuild index if ΔS ≥ 0.60 persists.

Copy-paste LLM guard prompt

I uploaded TXTOS and the WFGY Problem Map.

OCR provider: ABBYY (FineReader / FlexiCapture).  
Symptoms: field drift, unstable tables, ΔS ≥ 0.60.

Steps:
1. Identify failing layer (contracts, chunking, retrieval).  
2. Point to the WFGY fix page.  
3. Return JSON:  
   { "fields_checked": [...], "answer": "...", "ΔS": 0.xx, "λ_state": "<>", "next_fix": "..." }  
Keep it reproducible and auditable.

When to escalate

Field coverage < 0.70 even after re-chunk → Data Contracts
Persistent anchor drift → Chunking Checklist
Handwriting ΔS unstable across seeds → Entropy Collapse

🔗 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

🧭 Explore More

Module	Description	Link
WFGY Core	WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack	View →
Problem Map 1.0	Initial 16-mode diagnostic and symbolic fix framework	View →
Problem Map 2.0	RAG-focused failure tree, modular fixes, and pipelines	View →
Semantic Clinic Index	Expanded failure catalog: prompt injection, memory bugs, logic drift	View →
Semantic Blueprint	Layer-based symbolic reasoning & semantic modulations	View →
Benchmark vs GPT-5	Stress test GPT-5 with full WFGY reasoning suite	View →
🧙‍♂️ Starter Village 🏡	New here? Lost in symbols? Click here and let the wizard guide you through	Start →

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