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ProblemMap/GlobalFixMap/LanguageLocale/tokenizer_mismatch.md
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# Tokenizer Mismatch — Guardrails and Fix Pattern
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A focused fix when **embedder, retriever, reranker, and generator** do not share the same tokenization or normalization rules. Use this page to localize the failure, align the text pipeline, and verify with measurable targets.
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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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- End to end retrieval knobs: [retrieval-playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
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- Traceability and snippet schema: [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)
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- Payload schema and contracts: [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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- Language mixing and locale drift:
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[script_mixing.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LanguageLocale/script_mixing.md) ·
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[locale_drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LanguageLocale/locale_drift.md)
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- Tokenization and casing details:
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[tokenization_and_casing.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Embeddings/tokenization_and_casing.md) ·
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[normalization_and_scaling.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Embeddings/normalization_and_scaling.md)
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## When to use this page
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- High similarity to the right document but wrong snippet or misaligned offsets.
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- Same query returns different top-k after re-index or provider switch.
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- Citations do not line up with visible tokens in CJK or Indic scripts.
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- Mixed width or composed characters behave inconsistently after export.
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- Reranker improves precision but answers still drift in long chains.
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## Acceptance targets
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- ΔS(question, retrieved) ≤ 0.45 on three paraphrases.
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- Coverage of target section ≥ 0.70 with stable offsets.
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- λ remains convergent across two seeds after tokenizer lock.
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- Snippet offsets map to visible glyphs after NFC or NFKC pass.
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---
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## 60-second fix checklist
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1) **Identify tokenizers in play**
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Record for each stage: embedder, store analyzer, reranker, generator. Note version, normalization, casing, segmentation rules.
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2) **Normalize once, early**
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Apply one canonical pass for the corpus and the queries. Pick **NFC** for general Latin scripts. Pick **NFKC** when full-width, compatibility forms, or half-width punctuations appear. Keep the same pass for both corpus and queries.
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See: [normalization_and_scaling.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Embeddings/normalization_and_scaling.md)
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3) **Lock casing strategy**
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Either preserve case end to end or lower both sides before embedding. Do not mix.
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See: [tokenization_and_casing.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Embeddings/tokenization_and_casing.md)
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4) **Unify segmenter**
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CJK and Thai cannot rely on whitespace. Use the same segmenter for chunking and for query pre-processing. Validate offsets after segmentation.
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5) **Version the tokenizer**
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Store `TOKENIZER_FAMILY`, `TOKENIZER_VERSION`, `NORM_PASS` inside snippet metadata. Reject inserts that do not match.
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Spec fields live in: [data-contracts.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md)
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6) **Rebuild the index if needed**
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If ΔS stays high and offsets are unstable, rebuild with the aligned tokenizer and normalization. Verify with a small gold set.
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---
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## Symptom map → exact fix
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| Symptom | Likely cause | Open this |
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|---|---|---|
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| Citations jump inside CJK lines | chunker uses char windows, retriever uses wordpiece | [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) · [tokenization_and_casing.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Embeddings/tokenization_and_casing.md) |
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| Wrong-meaning hits with high cosine | incompatible normalization between corpus and query | [embedding-vs-semantic.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md) · [normalization_and_scaling.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Embeddings/normalization_and_scaling.md) |
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| BM25 improves, hybrid becomes worse | query split from mixed scripts or width | [script_mixing.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LanguageLocale/script_mixing.md) · [retrieval-playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md) |
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| Offsets do not align after PDF export | composed characters or soft hyphen artifacts | [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) |
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| Answers flip between runs | prompt headers reorder, λ becomes variant | [context-drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md) |
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---
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## Deep checks
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- **Normalization audit**
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Log a 1k sample of tokens from corpus and queries. Count deltas after NFC vs NFKC. Reject mismatches above 0.5 percent.
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- **Width and compatibility scan**
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Count full-width Latin, half-width katakana, ligatures, ZWJ, soft hyphen. Normalize or strip consistently.
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- **Segmenter parity**
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For CJK, Thai, Khmer, Lao, use the same dictionary for chunking and for query prep. Verify that `start_offset` and `end_offset` point to visible glyphs.
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- **Analyzer parity in the store**
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If the store applies analyzers, make them explicit. For Elastic or OpenSearch, pin the analyzer in the index template and document it in the snippet schema.
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- **Reranker bridge**
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If the retriever is sparse and the reranker is dense, ensure identical normalization happens before both. Otherwise reranker scores become unstable.
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---
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## Minimal reproducible test
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1) Pick three paraphrases of the same question.
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2) For each: compute ΔS(question, retrieved) and record λ state.
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3) Inspect offsets on the top snippet. Confirm visual alignment after normalization.
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4) Target: ΔS ≤ 0.45 and λ convergent on two seeds. Coverage ≥ 0.70 for the correct section.
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---
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## Copy-paste prompt
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```
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You have TXT OS and WFGY Problem Map loaded.
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My tokenizer issue:
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* corpus normalization: NFC or NFKC?
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* segmenter family and version for chunking vs query
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* store analyzer and reranker tokenizer
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* symptom: offsets drift, wrong-meaning hits, hybrid instability
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Tell me:
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1. the failing layer and why,
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2. the exact WFGY pages to open,
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3. the minimal steps to align tokenizer, normalization, and analyzers,
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4. a short test to verify with ΔS ≤ 0.45 and stable offsets.
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```
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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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