# Fallback Translation and Glossary Bridge · Global Fix Map
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When native-language recall keeps missing the right snippet, switch to a **controlled translation bridge** with a domain glossary and alias shield. Translate only where needed, protect entities and negations, and verify improvement with ΔS, λ, and coverage. --- ## Open these first * Visual map and recovery → [rag-architecture-and-recovery.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) * End to end retrieval knobs → [retrieval-playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md) * Traceability schema → [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) * Contract the payload → [data-contracts.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md) * Language overview → [multilingual\_guide.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/multilingual_guide.md) * Tokenizer variance → [tokenizer\_mismatch.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/tokenizer_mismatch.md) * Mixed scripts → [script\_mixing.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/script_mixing.md) * Locale normalization → [locale\_drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/locale_drift.md) * Romanization rules → [romanization\_transliteration.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/romanization_transliteration.md) * Proper nouns and aliases → [proper\_noun\_aliases.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/proper_noun_aliases.md) * Language detection → [query\_language\_detection.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/query_language_detection.md) * Analyzer routing → [query\_routing\_and\_analyzers.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/query_routing_and_analyzers.md) * Multilingual ranking → [hybrid\_ranking\_multilingual.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/hybrid_ranking_multilingual.md) * Bilingual eval sets → [code\_switching\_eval.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/code_switching_eval.md) * Stopwords and morphology → [stopword\_and\_morphology\_controls.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/stopword_and_morphology_controls.md) --- ## Core acceptance targets * ΔS(question, retrieved) ≤ 0.45 on three paraphrases and two seeds * Coverage of target section ≥ 0.70 * λ convergent after the bridge, across native vs pivot language * No entity corruption or negation loss in the final citation set * Rank\@k improves or remains flat after the bridge is enabled --- ## When to enable the bridge Enable only if all three hold: 1. Native path shows **flat-high ΔS** across k settings. 2. Query language and corpus language differ or the corpus is mixed locale. 3. Entity recall improves during a quick pivot test without harming citations. If any native pipeline item is obviously wrong, fix that first. See tokenizer, analyzer, or morphology pages above. --- ## What usually breaks | Symptom | Likely cause | Open this | | ----------------------------------------------- | ------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | Correct doc exists yet never ranks in top k | analyzer or tokenizer mismatch between query and store | [tokenizer\_mismatch.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/tokenizer_mismatch.md) · [query\_routing\_and\_analyzers.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/query_routing_and_analyzers.md) | | Names translate or transliterate inconsistently | missing alias shield or mixed romanization | [proper\_noun\_aliases.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/proper_noun_aliases.md) · [romanization\_transliteration.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/romanization_transliteration.md) | | Negations flip meaning after MT | no do-not-translate list for negation tokens | [stopword\_and\_morphology\_controls.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/stopword_and_morphology_controls.md) | | CJK queries degrade when pivoting via English | script segmentation and width rules differ by stage | [script\_mixing.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/script_mixing.md) | | Turkish/Greek accent fold changes matches | locale normalization not pinned per stage | [locale\_drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/locale_drift.md) | | Good recall but order is noisy across languages | reranker trained mono-lingual or features not aligned | [hybrid\_ranking\_multilingual.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/hybrid_ranking_multilingual.md) | --- ## Design: glossary bridge in two modes **Mode A — Query-side pivot** Translate the query to the corpus language with a **glossary and alias shield**. Run retrieval native to the store, then reason in user language. **Mode B — Corpus-side pivot** Keep query in user language, retrieve in native, but translate **candidate snippets** to the user language for reranking and reasoning. Never re-index on the pivot. **Glossary components** * **do\_not\_translate**: names, products, codes, unit strings, legal terms. * **preferred\_terms**: enforce a deterministic mapping for domain words. * **romanization\_map**: stable transliteration table with 1-to-N aliases. * **negation\_and\_modality**: tokens that must survive intact. * **protected\_char\_classes**: width, diacritics, punctuation class locks. **Trace fields to log** ``` { "bridge_mode": "A|B", "pivot_lang": "en|zh|..", "glossary_hash": "sha256:...", "alias_set_hash": "sha256:...", "ΔS_before": 0.xx, "ΔS_after": 0.yy, "coverage_before": 0.xx, "coverage_after": 0.yy } ``` --- ## Minimal implementation steps 1. **Detect language** Use the contract from [query\_language\_detection.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/query_language_detection.md). Refuse fallback if detection is unstable. 2. **Assemble glossary** * Pull domain terms. * Add aliases from [proper\_noun\_aliases.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/proper_noun_aliases.md). * Add romanization table from [romanization\_transliteration.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/romanization_transliteration.md). * Add negation and unit strings to do-not-translate. 3. **Choose mode** * Mode A if store is single-locale and analyzers are correct. * Mode B if store is mixed or analyzers cannot be changed. 4. **Run retrieval** Route analyzers per [query\_routing\_and\_analyzers.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/query_routing_and_analyzers.md). For Mode B, translate only candidates for reranking. 5. **Verify** Compute ΔS and coverage. Require λ convergent across two seeds and three paraphrases. Log trace fields. 6. **Publish** Keep the glossary versioned and pinned in eval reports. Guard with [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) and [data-contracts.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md). --- ## Spec: glossary JSON ```json { "version": "glossary_acme_finance_2025_08_30", "pivot_lang": "en", "do_not_translate": ["Value at Risk", "CAGR", "ROE", "İstanbul", "北京市", "§"], "preferred_terms": { "账面价值": "book value", "净现值": "net present value" }, "romanization_map": { "北京市": ["Beijing Shi", "Beijing City"], "İstanbul": ["Istanbul", "Stamboul"] }, "negation_and_modality": ["not", "never", "must", "should"], "protected_char_classes": ["fullwidth_digit", "narrow_no_break_space"] } ``` --- ## Copy-paste prompt for the LLM step ``` You have TXTOS and the WFGY Problem Map loaded. My multilingual issue: - native_lang: {xx} - user_lang: {yy} - mode: {A|B} - glossary: {do_not_translate, preferred_terms, romanization_map, negation_and_modality} - question: "{user_question}" - candidates: [{snippet_id, text, source_url}...] Do: 1) Apply the glossary strictly. Protect names, units, negations. 2) Perform cite-then-explain. If citations are weak, return the minimal fix and do not fabricate. 3) Return JSON: { "bridge_mode": "A|B", "pivot_lang": "en|...", "citations": [...], "answer": "...", "ΔS": 0.xx, "coverage": 0.xx, "λ_state": "→|←|<>|×", "next_fix": "..." } Keep it auditable and short. ``` --- ## Eval protocol * Use bilingual and code-switching sets from [code\_switching\_eval.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/code_switching_eval.md). * Compare native vs bridge on the same questions and seeds. * Accept only if ΔS ≤ 0.45, coverage ≥ 0.70, λ convergent, and entity recall does not regress. * Report deltas for Rank\@k and citation accuracy. --- ## Common gotchas * Translating the **index**. Never translate and re-index as a “quick fix”. Pivot only at query or candidate stage. * Letting the MT rewrite units or numbers. Add them to do-not-translate. * Dropping diacritics or width during translation. Pin normalization from [locale\_drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/locale_drift.md) and [script\_mixing.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/script_mixing.md). * Reranking with a mono-lingual model. If scores are noisy across languages, follow [hybrid\_ranking\_multilingual.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/hybrid_ranking_multilingual.md). --- ### 🔗 Quick-Start Downloads (60 sec) | Tool | Link | 3-Step Setup | | -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------- | | **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 + \” | | **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 | --- ### Explore More | Layer | Page | What it’s for | | --- | --- | --- | | ⭐ Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof | | ⚙️ Engine | [WFGY 1.0](/legacy/README.md) | Original PDF tension engine and early logic sketch (legacy reference) | | ⚙️ Engine | [WFGY 2.0](/core/README.md) | Production tension kernel for RAG and agent systems | | ⚙️ Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine (131 S class set) | | 🗺️ Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure taxonomy and fix map | | 🗺️ Map | [Problem Map 2.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card for RAG and agent pipeline diagnosis | | 🗺️ Map | [Problem Map 3.0](/ProblemMap/wfgy-ai-problem-map-troubleshooting-atlas.md) | Global AI troubleshooting atlas and failure pattern map | | 🧰 App | [TXT OS](/OS/README.md) | .txt semantic OS with fast bootstrap | | 🧰 App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q&A built on TXT OS | | 🧰 App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image generation with semantic control | | 🏡 Onboarding | [Starter Village](/StarterVillage/README.md) | Guided entry point for new users | If this repository helped, starring it improves discovery so more builders can find the docs and tools. 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