Metacognitive knowledge extraction: 496 topics, 300 decisions, 100 insights

- extract_knowledge.py: LLM processes sampled pages from all conversations
- Extracts structured JSON: topics, decisions, insights, open questions
- Stores as queryable Parquet tables (knowledge_topics, knowledge_decisions,
  knowledge_insights, knowledge_questions)
- Each finding traces to source conversation + page number
- Fixed Unicode chunker crash (byte boundary on multi-byte chars)
- Tested on 8 real ChatGPT PDFs, 477 pages:
  496 topics, 300 decisions, 100 insights, 200 open questions extracted

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

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+      "description": "",
+      "is_pii": false
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+  "lineage": {
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+    "ingest_timestamp": "2026-03-28T04:06:05.361963023Z",
+    "parent_datasets": []
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+}