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ProblemMap/GlobalFixMap/Language/query_routing_and_analyzers.md
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# Query Routing and Analyzers · Global Fix Map
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Bind detected `lang` and `script` to the right analyzer, tokenizer, and alias views. Keep the retriever, reranker, and LLM tokenizer in agreement so ΔS and λ stay stable across paraphrases and seeds.
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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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* End to end retrieval knobs → [retrieval-playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
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* Why this snippet → [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)
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* Contract the payload → [data-contracts.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md)
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* Tokenizer variance → [tokenizer\_mismatch.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/tokenizer_mismatch.md)
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* Mixed scripts in one query → [script\_mixing.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/script_mixing.md)
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* Locale normalization → [locale\_drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/locale_drift.md)
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* Proper noun aliases → [proper\_noun\_aliases.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/proper_noun_aliases.md)
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* Romanization rules → [romanization\_transliteration.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/romanization_transliteration.md)
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* Language detection → [query\_language\_detection.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/query_language_detection.md)
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---
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## Core acceptance targets
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* ΔS(question, retrieved) ≤ 0.45 across three paraphrases and two seeds
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* Coverage of target section ≥ 0.70
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* λ remains convergent when the same question is asked in native script and in romanized form
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* Analyzer choice and LLM tokenizer profile are logged and consistent across runs
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* No rank flip after switching analyzers on the same corpus
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---
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## Minimal routing contract
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**Detector input and result** from [query\_language\_detection.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/query_language_detection.md) gives:
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```
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lang, script, confidence, romanized_suspect, variants[]
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```
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**Routing decision** must produce:
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```
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analyzer_id # store analyzer for full-text field
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tokenizer_profile # retriever or LLM tokenizer profile name
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alias_views # which alias fields to probe (romanized, synonyms_local)
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hybrid_weights # bm25:vector ratio, or reranker on/off
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notes # short rationale for audit
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```
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You must log these five fields in the retrieval trace item along with ΔS and λ.
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---
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## Store routing matrix
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These are stable patterns, not vendor endorsements. Use them to avoid metric and analyzer mismatches.
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| Script | Primary choice | Alias view for romanized | Notes and links |
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| --------------------- | ------------------------------------------------- | ----------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| Latn | locale aware analyzer with ICU folding | none or localized synonyms | Keep case and diacritics decisions consistent. See [locale\_drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/locale_drift.md). |
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| Han, Hira, Kana, Hang | language specific analyzer or CJK bigram analyzer | `title_romaji`, `name_pinyin` | Mix of bigram and dictionary analyzers is fine if logged and deterministic. |
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| Cyrl | Cyrillic aware analyzer | optional translit alias | Keep transliteration only as alias view. Do not replace canonical text. |
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| Arab, Hebr | RTL analyzer with width and bidi guards | optional translit alias | Normalize digits and punctuation for the detector step only. |
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| Mixed scripts | two analyzers in parallel | romanized alias true | Enforce cite then explain in the answer. See [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md). |
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Store specifics you can cross check:
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* Elasticsearch guide → [elasticsearch.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/VectorDBs_and_Stores/elasticsearch.md)
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* Typesense guide → [typesense.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/VectorDBs_and_Stores/typesense.md)
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* Vespa guide → [vespa.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/VectorDBs_and_Stores/vespa.md)
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---
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## Typical failure → exact fix
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| Symptom | Likely cause | Open this |
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| ----------------------------------------------------------- | ------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| High similarity yet wrong meaning after switching analyzers | metric and analyzer mismatch | [embedding-vs-semantic.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md), [retrieval-playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md) |
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| Good recall but unstable rank in CJK | mixing bigram and dictionary analyzers without a fence | [script\_mixing.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/script_mixing.md) |
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| JSON mode breaks when analyzer changes | tokenizer profile not aligned with LLM’s expected JSON tokens | [tokenizer\_mismatch.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/tokenizer_mismatch.md) |
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| Romanized search finds no evidence | alias views missing or disabled | [romanization\_transliteration.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/romanization_transliteration.md) |
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| Brand name equals common word in another language | alias collision and unscoped synonyms | [proper\_noun\_aliases.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/proper_noun_aliases.md) |
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---
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## 60 second routing plan
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1. **Script first.** Use the detector output. If `confidence < 0.65`, route both native analyzer and romanized alias.
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2. **Lock tokenizer.** Choose a tokenizer profile that matches your retriever model and your LLM. Log it.
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3. **Hybrid weights.** Start with bm25\:vector at 0.4:0.6 and move by 0.1 until ΔS ≤ 0.45.
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4. **Cite then explain.** Force snippet fields in the native script when possible.
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5. **Regression gate.** Require coverage ≥ 0.70 on three paraphrases before deploy.
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---
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## Copy snippets
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**A. Router skeleton**
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```python
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def choose_route(det):
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routes = []
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if det["script"] in ["Han","Hira","Kana","Hang"]:
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routes.append({
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"analyzer_id": "store:cjk",
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"tokenizer_profile": "retriever:cjk",
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"alias_views": ["name_romaji","name_pinyin"],
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"hybrid_weights": [0.4, 0.6],
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"notes": "cjk primary"
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})
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elif det["script"] == "Cyrl":
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routes.append({
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"analyzer_id": "store:cyrl",
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"tokenizer_profile": "retriever:default",
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"alias_views": ["name_translit"],
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"hybrid_weights": [0.5, 0.5],
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"notes": "cyrillic"
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})
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elif det["script"] == "Arab":
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routes.append({
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"analyzer_id": "store:rtl",
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"tokenizer_profile": "retriever:default",
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"alias_views": ["name_translit"],
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"hybrid_weights": [0.5, 0.5],
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"notes": "rtl"
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})
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else:
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routes.append({
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"analyzer_id": "store:latn",
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"tokenizer_profile": "retriever:default",
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"alias_views": [],
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"hybrid_weights": [0.4, 0.6],
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"notes": "latin"
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})
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if det["confidence"] < 0.65 or det.get("romanized_suspect"):
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# add romanized alias probe for safety
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for r in routes:
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r["alias_views"] = sorted(set(r["alias_views"] + ["aliases_romanized"]))
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r["notes"] += " + alias probe"
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return routes
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```
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**B. Elasticsearch style mapping sketch**
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```json
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{
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"mappings": {
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"properties": {
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"body": { "type": "text", "analyzer": "cjk" },
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"title": { "type": "text", "analyzer": "cjk" },
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"name_pinyin": { "type": "text", "analyzer": "icu_analyzer" },
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"name_romaji": { "type": "text", "analyzer": "icu_analyzer" },
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"aliases_romanized": { "type": "text", "analyzer": "icu_analyzer" },
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"section_id": { "type": "keyword" }
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}
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}
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}
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```
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**C. Typesense style fields**
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```json
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{
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"name": "docs",
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"fields": [
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{"name":"body","type":"string","locale":"zh"},
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{"name":"title","type":"string","locale":"zh"},
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{"name":"aliases_romanized","type":"string[]","locale":"en"},
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{"name":"section_id","type":"string","facet":true}
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]
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}
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```
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**D. Vespa schema sketch**
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```
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schema docs {
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document docs {
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field body type string { indexing: summary | index }
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field title type string { indexing: summary | index }
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field aliases_romanized type array<string> { indexing: summary | index }
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}
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fieldset default { fields: body, title }
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rank-profile default { first-phase { expression: bm25(body) + bm25(title) } }
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}
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```
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---
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## Eval plan
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* Use the sets from [code\_switching\_eval.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/code_switching_eval.md).
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* Add pairs of queries in native script and romanized forms for the same entity.
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* Targets: ΔS ≤ 0.45, coverage ≥ 0.70, λ convergent on two seeds.
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* If rank flips between analyzers, clamp with a deterministic reranker and verify with [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md).
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---
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## When to escalate
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* ΔS stays ≥ 0.60 after analyzer swap → rebuild index with fixed analyzer and verify metric in [retrieval-playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md).
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* Instability only in long chains → treat as reasoning issue and apply BBCR bridge, see [logic-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/logic-collapse.md).
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---
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## Copy paste prompt for the LLM step
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```
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You have TXTOS and the WFGY Problem Map loaded.
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Given detector output {lang, script, confidence, romanized_suspect}:
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1) Choose analyzer and tokenizer profile deterministically.
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2) If confidence < 0.65 or romanized_suspect=true, search the romanized alias view as well.
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3) Cite-then-explain from the native script snippet when possible.
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4) Return a JSON trace:
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{ "analyzer_id": "...", "tokenizer_profile": "...", "alias_views": [...], "ΔS": 0.xx, "λ_state": "→|←|<>|×" }
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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)** <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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