WFGY/ProblemMap/GlobalFixMap/Language/multilingual_guide.md

6.8 KiB
Raw Blame History

Multilingual Guide — Guardrails and Fix Patterns

🧭 Quick Return to Map

You are in a sub-page of Language.
To reorient, go back here:

Think of this page as a desk within a ward.
If you need the full triage and all prescriptions, return to the Emergency Room lobby.

A compact field guide to stabilize multilingual RAG across CJK, RTL, mixed scripts, and locale drift. Use this page to check symptoms, apply structural fixes, and verify with measurable targets.


Open these first


Core acceptance

  • ΔS(question, retrieved) ≤ 0.45 across at least 2 languages
  • Coverage ≥ 0.70 for the target section in each language
  • λ remains convergent across three paraphrases in mixed scripts
  • E_resonance stays flat for long bilingual/RTL runs

Common multilingual failure modes

Symptom Likely cause Open this
Retrieval drops snippets when query is in Chinese or Japanese Tokenizer mismatch (no whitespace segmentation) tokenizer_mismatch.md
Citations collapse when Arabic/Hebrew text mixes with English Script directionality conflict script_mixing.md
High similarity but meaning flips across locale Locale analyzer mismatch (stemming / stopwords) locale_drift.md
HyDE/BM25 retrieval different per language Query expansion language bias hyde_multilingual.md

Fix in 60 seconds

  1. Probe with ΔS Run the same question in English and one target language. If ΔS differs by >0.15, suspect tokenization or analyzer mismatch.

  2. Apply λ_observe Paraphrase the query three ways in the non-English language. If λ diverges, enforce schema lock and re-index with language-specific analyzers.

  3. Structural repair


Diagnostic checklist

  • Tokenizer: verify segmentation strategy (whitespace vs character-level)
  • Analyzer: confirm stemming and stopword lists match query language
  • Scripts: normalize Unicode, check RTL/LTR flags
  • Locale drift: run same snippet under two locales, compare ΔS
  • Hybrid retriever: ensure rerankers operate on normalized embeddings

🔗 Quick-Start Downloads (60 sec)

Tool Link 3-Step Setup
WFGY 1.0 PDF Engine Paper 1 Download · 2 Upload to your LLM · 3 Ask “Answer using WFGY + <your question>”
TXT OS (plain-text OS) TXTOS.txt 1 Download · 2 Paste into any LLM chat · 3 Type “hello world” — OS boots instantly

Explore More

Module Description Link
WFGY Core Canonical framework entry point View
Problem Map Diagnostic map and navigation hub View
Tension Universe Experiments MVP experiment field View
Recognition Where WFGY is referenced or adopted View
AI Guide Anti-hallucination reading protocol for tools View

If this repository helps, starring it improves discovery for other builders.
GitHub Repo stars