WFGY/ProblemMap/GlobalFixMap/Language

Language & Multilingual — Global Fix Map

A compact hub to stabilize cross-lingual retrieval and reasoning. Use this folder when your corpus or queries span CJK, RTL, Indic, Cyrillic, accented Latin, or when users code-switch.

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Quick routes to per-page guides

• Tokenizer mismatch → tokenizer_mismatch.md
• Script mixing in one query → script_mixing.md
• Locale drift and normalization → locale_drift.md
• End-to-end overview and recipes → multilingual_guide.md

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When to use this folder

• High similarity yet wrong meaning on bilingual or mixed-script corpora
• Citations point to the wrong section after translating the question
• Hybrid retrievers underperform a single retriever across languages
• Index “looks” healthy while coverage remains low for non-Latin scripts
• Names flip between native, transliteration, and English aliases
• zh-Hans and zh-Hant never co-retrieve, Thai recall collapses without clear reason

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Acceptance targets

• ΔS(question, retrieved) ≤ 0.45 across language variants
• Coverage of the target section ≥ 0.70 after repair
• λ remains convergent across three paraphrases and two seeds
• E_resonance stays flat on long windows that mix scripts

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Open these first

• Visual map and recovery → rag-architecture-and-recovery.md
• End-to-end retrieval knobs → retrieval-playbook.md
• Why this snippet, how to cite → retrieval-traceability.md
• Snippet schema fence → data-contracts.md
• Embedding vs meaning → embedding-vs-semantic.md
• Chunk boundary sanity → chunking-checklist.md

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Map symptoms → structural fixes (Problem Map)

Symptom	Likely cause	Open this
Wrong-meaning hits despite high similarity	Embedding not multilingual or pre-norm mismatch	embedding-vs-semantic.md
Citations jump sections after translation	Snippet schema too loose	data-contracts.md, retrieval-traceability.md
zh-Hans/zh-Hant never co-retrieve	Variant mapping missing	locale_drift.md
Thai/CJK recall collapses	Tokenizer mismatch, missing segmenter	tokenizer_mismatch.md
Mixed Latin + CJK query under-recalls	Analyzer split across scripts	script_mixing.md
Hybrid retriever worse than single	Query parsing split, mis-weighted rerank	patterns/pattern_query_parsing_split.md, rerankers.md

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Fix in 60 seconds

1. Measure ΔS across variants Run question in source language, target language, and a code-switched version. If ΔS improves only after transliteration or segmentation, language handling is the failing layer.

2. Probe λ_observe Hold citations fixed and flip only script or segmentation. If λ flips, lock schema and unify analyzers.

3. Apply the smallest change

• Unify index and search analyzers, add Thai/CJK segmenters
• Map zh-Hans ↔ zh-Hant at ingest or store in variant subfields
• Add alias fields for proper nouns: native, romanized, normalized
• Normalize digits, punctuation, and diacritics for RTL/Indic consistently
• Use a multilingual embedding; otherwise add a lexical sidecar and deterministic rerank

4. Verify Coverage ≥ 0.70 and ΔS ≤ 0.45 across two languages and one mixed query. λ convergent on two seeds.

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Store-agnostic quick recipes

• Elasticsearch/OpenSearch: ICU normalization, width fold, bigram analyzers for CJK, Thai segmenter, keyword subfields for product names.
• Vector stores: pre-normalize identically for corpus and queries, validate with a bilingual gold set, rerank deterministically if embeddings are monolingual.

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🔗 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

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🧭 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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