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193 lines
11 KiB
Markdown
193 lines
11 KiB
Markdown
# Script Mixing — Guardrails and Fix Patterns
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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 **Language**.
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> To reorient, go back here:
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>
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> - [**Language** — multilingual processing and semantic alignment](./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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Keep retrieval stable when a single query or snippet mixes scripts and directions.
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Common cases: CJK + Latin acronyms, Arabic or Hebrew with numbers and English terms, Devanagari with Latin product names, and datasets where full-width digits appear beside half-width ASCII.
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---
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## Open these first
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* Visual map and recovery: [rag-architecture-and-recovery.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md)
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* Why this snippet and how to cite: [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)
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* Snippet schema fence: [data-contracts.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md)
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* Embedding vs meaning: [embedding-vs-semantic.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md)
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* Chunk boundary sanity: [chunking-checklist.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md)
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Related in this folder:
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* Tokenization drift: [tokenizer\_mismatch.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/tokenizer_mismatch.md)
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* Locale and analyzer drift: [locale\_drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/locale_drift.md)
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* Multilingual guide hub: [multilingual\_guide.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/multilingual_guide.md)
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* HyDE behavior by language: [hyde\_multilingual.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/hyde_multilingual.md)
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---
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## Core acceptance targets
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* ΔS(question, retrieved) ≤ 0.45 for mixed-script queries
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* Coverage of the target section ≥ 0.70 after repair
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* λ remains convergent across three paraphrases that include different script orderings
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* E\_resonance flat on long windows with numerals, punctuation, and brand names mixed in
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---
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## What this failure looks like
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| Symptom | Likely cause | Where to fix |
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| ---------------------------------------------------------------- | --------------------------------------------------------------------------- | -------------------------------------------------------------------------------- |
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| Arabic or Hebrew queries return partial hits or broken citations | Bidirectional marks and numerals flip visual order; analyzer not bidi-aware | Normalize directionality and digits before indexing and querying |
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| CJK text with Latin acronyms splits unpredictably | Mixed width digits, zero-width chars, or inconsistent spacing rules | Pre-normalize width, strip zero-width, add script-boundary spacing for embedding |
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| English brand + Thai sentence retrieves far sections | Different analyzers per stage cause token joins and drops | Unify analyzer and pre-segment at script transitions |
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| High similarity but wrong meaning on acronyms | Casing and width normalization inconsistent between corpus and query | Apply the same ASCII, width, and case rules in both pipelines |
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---
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## Fix in 60 seconds
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1. **Measure ΔS**
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Run the original mixed-script query and a variant where scripts are separated by spaces. If ΔS improves by ≥ 0.10, you have a script-mixing normalization gap.
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2. **Probe λ\_observe**
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Swap the order of scripts in the query, keep semantics identical. If λ flips or citations jump, lock prompt headers and fix normalization and analyzer alignment first.
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3. **Apply the smallest structural change**
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* Normalize Unicode to NFC, convert full-width to half-width for digits and ASCII.
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* Remove zero-width characters, directional isolates from raw text.
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* Ensure the same analyzer is used for both index and query, or pre-segment before embedding.
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4. **Verify**
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Coverage ≥ 0.70 and ΔS ≤ 0.45 on three paraphrases with different script orders.
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---
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## Minimal repair recipes by stack
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### Elasticsearch / OpenSearch
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* Use ICU chain for mixed scripts. Typical pipeline:
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`icu_normalizer` (NFC) → `icu_transform` (full-width to half-width) → `icu_folding` → optional CJK bigram filter.
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* For Arabic or Persian add `arabic_normalization` or `persian_normalization`.
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* Strip bidi control chars in a char filter.
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* Set the same analyzer for `index` and `search_analyzer` on the field.
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* Create a keyword subfield for exact acronyms and model names.
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Reference: [retrieval-playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
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### BM25 in code or light stores
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* Preprocess text with a normalization step that performs:
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Unicode NFC, width fold for digits and ASCII, lowercasing where safe, removal of zero-width and bidi marks.
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* For CJK, insert temporary spaces at script boundaries or use character bigrams for both index and query.
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* Keep identical punctuation rules across stages.
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Open: [pattern\_query\_parsing\_split.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_query_parsing_split.md)
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### Vector stores (FAISS, Milvus, Qdrant, Weaviate, pgvector)
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* Normalize text before embedding with the same script rules for corpus and queries.
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* Add lightweight lexical recall (BM25) to catch brand names and numerals, then rerank deterministically.
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* Re-embed only a gold slice to validate, then batch the full rebuild.
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Open: [vectorstore-fragmentation.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_vectorstore_fragmentation.md)
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---
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## Diagnostic checklist
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* The same normalization code runs for ingest and query.
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* Width folding, casing, digit policy are identical across stages.
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* Bidi control marks removed or isolated consistently.
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* Chunk boundaries do not split inside script transitions that carry meaning.
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* Rerank stage views the normalized text, not raw captures.
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---
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## Copy-paste tests
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**Script order probe**
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```
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Q0: original mixed-script query
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Q1: same words, scripts reordered
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Q2: same words, add spaces at script boundaries
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Return a table with ΔS per query, λ_state, and whether citations stayed in the same section.
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```
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**Bidi and width sanity**
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```
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Given a sentence with Arabic text, ASCII digits, and an English acronym:
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1) Remove bidi marks and normalize widths.
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2) Show the token sequence used by the retriever.
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3) Verify that numbers appear in logical order and acronyms stay intact.
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```
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---
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## When to escalate
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* ΔS remains ≥ 0.60 after normalization and analyzer unification.
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Re-chunk with stable boundaries and re-embed a gold slice.
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Open: [chunking-checklist.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md)
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* Citations still jump between sections on mixed-script inputs.
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Enforce snippet schema and forbid cross-section reuse.
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Open: [data-contracts.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md), [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)
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* Hybrid retrieval underperforms a single retriever.
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Align normalization rules before rerank, and make rerank deterministic.
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Open: [rerankers.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md)
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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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<!-- WFGY_FOOTER_START -->
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### Explore More
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| Layer | Page | What it’s for |
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| --- | --- | --- |
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| Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof |
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| Engine | [WFGY 1.0](/legacy/README.md) | Original PDF based tension engine |
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| Engine | [WFGY 2.0](/core/README.md) | Production tension kernel and math engine for RAG and agents |
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| Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine, 131 S class set |
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| Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure checklist and fix map |
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| Map | [Problem Map 2.0](/ProblemMap/rag-architecture-and-recovery.md) | RAG focused recovery pipeline |
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| Map | [Problem Map 3.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card, image as a debug protocol layer |
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| Map | [Semantic Clinic](/ProblemMap/SemanticClinicIndex.md) | Symptom to family to exact fix |
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| Map | [Grandma’s Clinic](/ProblemMap/GrandmaClinic/README.md) | Plain language stories mapped to Problem Map 1.0 |
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| Onboarding | [Starter Village](/StarterVillage/README.md) | Guided tour for newcomers |
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| App | [TXT OS](/OS/README.md) | TXT semantic OS, fast boot |
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| App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q and A built on TXT OS |
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| App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image with semantic control |
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| App | [Blow Blow Blow](/OS/BlowBlowBlow/README.md) | Reasoning game engine and memory demo |
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If this repository helped, starring it improves discovery so more builders can find the docs and tools.
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[](https://github.com/onestardao/WFGY)
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<!-- WFGY_FOOTER_END -->
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