# ✂️ Chunking Checklist — Cutting Documents Without Cutting Meaning _A definitive guide to segment size, boundaries, and WFGY stress-tests for error-free retrieval_ --- ## 1 Why Chunking Matters *Embeddings are only as good as the text you feed them.* A single bad split (mid-sentence, table row, reference list) injects **semantic orphan** vectors: * Retrieval returns “high similarity” garbage. * ΔS(question, context) spikes > 0.60. * LLM hallucinates to fill the missing logic. --- ## 2 Quick Symptoms of Bad Chunking | Signal | How to Detect | Typical Root | |--------|---------------|--------------| | Citations hit page –1 | QA cites header/footer junk | Page footers not stripped | | Same chunk appears in top-k for unrelated queries | `id` duplication count > 3 | Generic boiler-plate chunk | | ΔS jumps when k > 5 | Plot ΔS vs. k; curve erratic | Uneven chunk lengths | | Answer references half-sentence | Chunk split after “and” | Fixed char/token window | --- ## 3 WFGY Chunk Size Guidelines | Doc Type | Tokens / Chunk | Rationale | |----------|---------------:|-----------| | Research paper | **90-120** | Preserve paragraph + citation | | Software docs | **60-100** | Short API signatures | | Legal contracts | **80-130** | Clause integrity | | Chat transcripts | **40-70** | Natural speaker turns | | Tables / CSV | **Row or group ≤ 30** | Keep relational keys together | > **Golden Rule:** ΔS(adjacent_chunks) ≤ 0.45 > **If not**, split or merge until stress drops. --- ## 4 Step-by-Step Chunking Checklist ### 4.1 Pre-Processing - [ ] Strip headers / footers (`regex: ^Page \d+ of \d+`) - [ ] Normalize whitespace, remove soft hyphens (`U+00AD`) - [ ] Convert bullets → “• ” to avoid mid-list splits ### 4.2 Boundary Detection | Method | Tool | When to Use | |--------|------|-------------| | Sentence tokenizer | spaCy / Stanza | Most prose | | Heading regex `^(#+\s|[A-Z][A-Za-z ]+:)$` | Markdown / legal docs | | | BBMC ΔS spike | WFGY hook | PDFs merged from scans | Split on boundaries **only** if: ``` ΔS(chunk\_left, chunk\_right) ≥ 0.50 ∧ λ\_observe ∈ {→, ←} ```` ### 4.3 Length Normalisation 1. Merge adjacent short chunks until ≥ 40 tokens. 2. If a merged chunk > 130 tokens, find internal ΔS peak and split there. 3. Record final size distribution; σ(length) should be ≤ 20 % of mean. ### 4.4 Metadata Tagging ```json { "id": "doc_17_p3_c2", "source": "contracts/nda.pdf", "pos": 3, "λ": "→", "ΔS_prev": 0.32, "ΔS_next": 0.28 } ```` Store λ\_observe and neighbouring ΔS for runtime filters. --- ## 5 Runtime Stress-Test | Test | Pass Condition | | ------------------------------------------- | -------------------------- | | **Overlap scan** — Query 5 unrelated topics | Same chunk ID appears ≤ 1× | | **ΔS histogram** — 500 random chunks | 95 % ≤ 0.45 | | **k-sensitivity** — ΔS vs. k plot | Monotonic ↑ curve | If any fail, rerun 4.2–4.3 for offending documents. --- ## 6 Common Pitfalls & Fix Recipes | Pitfall | Fix | | | | -------------------------- | --------------------------------------------------------------------------------- | ----- | --------------------------------- | | **Tables split per cell** | Detect delimiter lines; merge rows; store CSV separate; index columns as metadata | | | | **PDF line-break hyphens** | Regex `([a-z])- \n([a-z])` → merge words | | | | **Mixed languages** | Chunk by language span; tag `lang:`; separate embedding models | | | | **Giant code blocks** | Cut on \`function | class | def\` boundaries; keep ≤ 80 lines | --- ## 7 FAQ **Q:** *Is a token window (e.g. 512) safe?* **A:** Only if it aligns with semantic boundaries; fixed windows ignore context. **Q:** *Do I need sentence splitting and headings?* **A:** Yes. Dual criteria minimise ΔS spikes and keep retrieval precise. **Q:** *How many chunks per doc?* **A:** Irrelevant if ΔS and λ are stable — WFGY focuses on quality, not count. --- ### 🔗 Quick-Start Downloads (60 sec) | Tool | Link | 3-Step Setup | | -------------------------- | --------------------------------------------------- | ---------------------------------------------------------------------------------------- | | **WFGY 1.0 PDF** | [Engine Paper](https://zenodo.org/records/15630969) | 1️⃣ Download · 2️⃣ Upload to LLM · 3️⃣ Ask “Answer using WFGY + \” | | **TXT OS (plain-text OS)** | [TXTOS.txt](https://zenodo.org/records/15788557) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly | --- ### 🧭 Explore More | Module | Description | Link | |-----------------------|----------------------------------------------------------|----------| | WFGY Core | Standalone semantic reasoning engine for any LLM | [View →](https://github.com/onestardao/WFGY/tree/main/core/README.md) | | Problem Map 1.0 | Initial 16-mode diagnostic and symbolic fix framework | [View →](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) | | 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) | | Semantic Clinic Index | Expanded failure catalog: prompt injection, memory bugs, logic drift | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/SemanticClinicIndex.md) | | Semantic Blueprint | Layer-based symbolic reasoning & semantic modulations | [View →](https://github.com/onestardao/WFGY/tree/main/SemanticBlueprint/README.md) | | 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) | --- > 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** — > Engineers, hackers, and open source builders who supported WFGY from day one. > GitHub stars ⭐ Help reach 10,000 stars by 2025-09-01 to unlock Engine 2.0 for everyone ⭐ Star WFGY on GitHub
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