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Create romanization_transliteration.md
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ProblemMap/GlobalFixMap/Language/romanization_transliteration.md
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ProblemMap/GlobalFixMap/Language/romanization_transliteration.md
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# Romanization & Transliteration — Guardrails and Fix Pattern
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Make cross-script search and RAG stable when users type Latin transliterations of non-Latin names and terms. This page gives a minimal contract, store wiring, and tests so **Hepburn vs Kunrei**, **Pinyin vs mixed tone marks**, **RR vs MR**, **ISO9 vs GOST**, **Buckwalter vs ISO 233**, and similar systems do not break recall or flip ranking.
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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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* Traceability and cite-then-explain → [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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* Embedding vs meaning → [embedding-vs-semantic.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.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 and width/diacritics → [locale\_drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/locale_drift.md)
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* Names and brand aliases → [proper\_noun\_aliases.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/proper_noun_aliases.md)
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* End to end multilingual playbook → [multilingual\_guide.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/multilingual_guide.md)
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---
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## Core acceptance targets
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* ΔS(question, retrieved) ≤ 0.45 for native script, romanized, and accent-stripped variants
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* Coverage of target section ≥ 0.70 under three paraphrases and two seeds
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* λ remains convergent when switching romanizers inside the same language
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* No false merges across entities when romanized forms collide
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---
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## Minimal contract
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Add a small, explicit layer around romanization so behavior is auditable.
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**Document side fields**
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```
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raw_text # untouched source
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lang # BCP-47 primary tag
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script # ISO 15924 (Han, Cyrl, Arab, Hira, Kana, Hang, etc.)
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canonical # preferred display form for proper nouns if known
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alias_tail # pipe-joined alias list incl. romanized forms
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romanizers # systems observed for this doc: "pinyin|rr|hepburn|iso9|buckwalter"
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```
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**Query side context**
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```
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q_text # user input
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q_lang_guess # detector result, nullable
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q_script_guess # detector result, nullable
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q_romanizer_hint # optional, from UI or logs, e.g. "hepburn"
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```
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**Rules**
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* Never mutate `raw_text` or `canonical`.
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* Romanized strings live only in `alias_tail` and store-specific synonym views.
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* Record which systems were used. Mixing systems without a record increases ΔS variance.
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---
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## Store wiring
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**BM25 style indexes**
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* Keep `raw_text` with a locale-aware analyzer.
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* Add a **synonym graph** on a separate field that contains romanized aliases.
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* Apply **width normalization** and **diacritic strip** only in alias field. Keep canonical untouched. See [locale\_drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/locale_drift.md).
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**Vector stores**
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* Append `alias_tail` to the chunk text right after the first canonical mention.
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* Keep short, high precision alias lists. Over-expansion harms meaning.
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* If nearest neighbors look similar yet wrong, verify metric per [embedding-vs-semantic.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md).
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**Hybrid**
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* When BM25 yields an exact canonical match, bias reranker features to keep it above looser transliterations.
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* Log ΔS and λ per candidate so you can see when a romanized neighbor outranks the native script without evidence.
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---
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## System map (examples)
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| Language | Common systems | Notes |
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| -------------------- | ----------------------------- | ---------------------------------------------------------------------------------- |
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| Chinese | Pinyin (tone marks or digits) | Keep tone-less aliases for user input, but preserve tone marks in canonical forms. |
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| Japanese | Hepburn, Kunrei, Nihon | Handle long vowels (ō vs ou) and small tsu. |
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| Korean | RR (Revised Romanization), MR | Names often appear without hyphens, add both. |
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| Russian and Cyrillic | ISO 9, GOST, BGN/PCGN | Map soft sign and yo/ë variants. |
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| Arabic | Buckwalter, ISO 233, DMG | Decide on hamza and taa marbuta conventions, keep both if present in corpus. |
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| Hebrew | SBL, Academy rules | Deal with mater lectionis and dagesh normalization. |
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| Hindi and Indic | ITRANS, ISO 15919 | Normalize nukta forms. |
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Keep this list in code comments and in your ops runbook, not only in the model prompt.
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---
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## Typical failure → fix
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| Symptom | Likely cause | Open this |
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| --------------------------------------------------- | -------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------- |
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| Native script doc exists, romanized query misses it | no alias view built at index time | [retrieval-playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md) |
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| Romanized neighbor outranks exact canonical snippet | reranker features not constrained | [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) |
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| Answers flip between Hepburn and Kunrei inputs | mixed systems without logging, λ not clamped | [tokenizer\_mismatch.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/tokenizer_mismatch.md) |
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| Cyrillic ISO9 vs GOST produce different chunks | analyzer mismatch per field | [locale\_drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/locale_drift.md) |
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| Arabic Buckwalter forms merge two entities | alias collision, missing scope fence | [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 fix checklist
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1. **Wire alias view** for documents that carry non-Latin scripts.
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2. **Record the system** used for any generated alias.
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3. **Normalize only in alias fields** for width and diacritics, never in canonical.
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4. **Bias reranker** to keep exact canonical hits above loose translits.
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5. **Log ΔS and λ** for native vs romanized queries and compare.
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---
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## Copy snippets
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**Alias expansion at ingest time (no external libs)**
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```python
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def simple_pinyin_drop_tones(s: str) -> str:
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tone_map = str.maketrans("āáǎàēéěèīíǐìōóǒòūúǔùǖǘǚǜü", "aaaaeeeeiiiioooouuuuuuuuu")
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return s.translate(tone_map)
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def width_fold(s: str) -> str:
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# simple NFKC fold
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import unicodedata as ud
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return ud.normalize("NFKC", s)
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def alias_pack(canonical: str, lang: str, romanizer_hint: str | None = None) -> list[str]:
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out = {canonical}
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if lang == "zh":
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out.add(simple_pinyin_drop_tones(canonical))
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# add more light rules per language as needed
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return [width_fold(x) for x in out]
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```
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**Prompt fence for romanizers**
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```
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You have TXTOS and the WFGY Problem Map.
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When the question or snippet contains a non-Latin name or term:
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1) Try native script first. If the user input looks romanized, search both native and alias views.
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2) Keep the canonical form in the final answer. Cite the exact snippet that contains the canonical form.
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3) If multiple romanization systems match, state which system appears in the cited text.
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```
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---
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## Eval plan
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Use a **code-switching set** with 5 languages and 10 entities each. For every entity build 3 questions:
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1. native script,
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2. romanized in system A,
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3. romanized in system B.
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Run the suite with [code\_switching\_eval.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Language/code_switching_eval.md).
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Targets
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* top-k 10 recall across forms ≥ 0.85
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* ΔS(question, retrieved) ≤ 0.45 on the best hit
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* λ convergent across two seeds and three paraphrases
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If recall is fine but ranking flips between systems, tighten reranker constraints 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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### 🔗 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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