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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+  "name": "knowledge_topics",
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+  "objects": [
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+      "key": "datasets/knowledge_topics.parquet",
+      "size_bytes": 14252,
+      "created_at": "2026-03-28T04:06:05.358571822Z"
+    }
+  ],
+  "created_at": "2026-03-28T04:06:05.358572461Z",
+  "updated_at": "2026-03-28T04:06:05.358833280Z",
+  "description": "",
+  "owner": "",
+  "sensitivity": null,
+  "columns": [
+    {
+      "name": "conversation",
+      "data_type": "Utf8",
+      "sensitivity": null,
+      "description": "",
+      "is_pii": false
+    },
+    {
+      "name": "page",
+      "data_type": "Int64",
+      "sensitivity": null,
+      "description": "",
+      "is_pii": false
+    },
+    {
+      "name": "topic",
+      "data_type": "Utf8",
+      "sensitivity": null,
+      "description": "",
+      "is_pii": false
+    }
+  ],
+  "lineage": {
+    "source_system": "csv",
+    "source_file": "knowledge_topics.csv",
+    "ingest_job": "ingest-1774670765358",
+    "ingest_timestamp": "2026-03-28T04:06:05.358571822Z",
+    "parent_datasets": []
+  },
+  "freshness": null,
+  "tags": [],
+  "row_count": 496
+}