{
"event": "PreToolUse",
"tool_name": "Read",
"tool_input": {
"file_path": "\/var\/www\/scripts\/pipeline\/backfill_knowledge_semantics.py",
"limit": 30
}
}
{
"tool_response": {
"type": "text",
"file": {
"filePath": "\/var\/www\/scripts\/pipeline\/backfill_knowledge_semantics.py",
"content": "#!\/usr\/bin\/env python3\n\"\"\"\nBackfill Knowledge Semantics for existing entities.\n\nAnalyzes all entities that don't have knowledge_semantics yet.\nResume-capable: skips already analyzed entities.\n\nUsage:\n python backfill_knowledge_semantics.py # Process all pending\n python backfill_knowledge_semantics.py --limit 100 # Process max 100\n python backfill_knowledge_semantics.py --batch 25 # Batch size 25\n python backfill_knowledge_semantics.py --dry-run # Just count, don't process\n\"\"\"\n\nimport argparse\nimport json\nimport time\n\nimport ollama\n\nfrom db import db\n\n# Valid ENUM values for validation\nVALID_SEMANTIC_ROLES = {\"agent\", \"patient\", \"instrument\", \"location\", \"cause\", \"effect\"}\nVALID_FUNCTIONAL_CATEGORIES = {\"method\", \"tool\", \"concept\", \"actor\", \"outcome\", \"process\"}\n\nPROMPT_TEMPLATE = \"\"\"Analysiere die Bedeutung dieser Entität im Kontext.\n\nEntität: {name}\nTyp: {entity_type}",
"numLines": 30,
"startLine": 1,
"totalLines": 290
}
}
}