feat(pipeline): MC Quality Overhaul — 74.5% → 92.8% accuracy, 5.3K → 13.6K MCs
Phase 0: Quality Audit script (Claude Sonnet, 1750 samples)
Phase 1: Object ontology expanded 31 → 74 tokens with descriptions + boundaries
Phase 2: 174K controls re-classified via Haiku (10 batches, $50)
- Generic tokens removed (documentation, procedure, process)
- L2 sub-topics added (108K + 64K controls)
- Bad subtopics fixed (stakeholder_*, escalation fragments)
Phase 3: Re-clustering K=18704 (37K objects → 16.7K groups)
Phase 4: Direct MC generation from canonical tokens (gpre2_direct_mc.py)
Phase 5: Regulation-source split (gpre3, dry-run tested)
New features:
- Tenant-isolated document upload API (rag-service)
- BAuA crawler (Playwright, 131 PDFs downloaded)
- OSHA Technical Manual crawler (23 chapters)
- CE obligation extractor (6141 obligations from Qdrant)
RAG ingestion:
- 126 BAuA PDFs (TRBS/TRGS/ASR): 27,664 chunks
- OSHA Technical Manual: 7,241 chunks
- OSHA 1910 Subpart O (full): 745 chunks
- EuGH C-588/21 P: 216 chunks
- EU 2018/1725: 842 chunks
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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