{
"event": "PreToolUse",
"tool_name": "Grep",
"tool_input": {
"pattern": "def step_|def run_step|entity_extract",
"path": "\/var\/www\/scripts\/pipeline",
"output_mode": "content",
"-n": true
}
}
{
"tool_response": {
"mode": "content",
"numFiles": 0,
"filenames": [],
"content": "knowledge\/__init__.py:17:from .entity_extractor import EntityExtractor\nknowledge\/analyzer.py:9:from .entity_extractor import EntityExtractor\nknowledge\/analyzer.py:42: self.entity_extractor = EntityExtractor(self.llm, self.storage.store)\nknowledge\/analyzer.py:49: return self.entity_extractor.extract_entities(text, level, source_id)\ndb.py:286: use_case: The use case (entity_extraction, semantic_analysis, statement_extraction, etc.)\ndb.py:687: pipeline_step: Optional step name (e.g., 'entity_extract')\nconfig\/entity_extraction_baseline.yaml:69: entity_extraction:\nconfig\/entity_extraction_baseline.yaml:70: name: \"entity_extraction\"\nconfig\/entity_extraction_baseline.yaml:71: use_case: \"entity_extraction\"\nanalyzers\/__init__.py:9:from .entity_extractor import extract_entities_anthropic, extract_entities_ollama, find_entity_by_name, store_entities\nanalyzers\/entity_extractor.py:194: pass1_template = db.get_prompt(\"entity_extraction_pass1\")\nanalyzers\/entity_extractor.py:195: pass2_template = db.get_prompt(\"entity_extraction_pass2\")\nanalyzers\/entity_extractor.py:227: request=f\"[entity_extraction_pass1] {len(valid_entities)} entities\",\nanalyzers\/entity_extractor.py:252: request=f\"[entity_extraction_pass2] categorize {len(valid_entities)} entities\",\nanalyzers\/entity_extractor.py:290: prompt_data = db.get_prompt_by_use_case(\"entity_extraction\")\nanalyzers\/entity_extractor.py:294: db.log(\"WARNING\", \"entity_extraction prompt not found in DB, using fallback\")\nanalyzers\/entity_extractor.py:310: request=f\"[entity_extraction] {prompt[:500]}...\",\nanalyzers\/entity_extractor.py:332: prompt_data = db.get_prompt_by_use_case(\"entity_extraction\")\nanalyzers\/entity_extractor.py:365: request=f\"[entity_extraction] {prompt[:500]}...\",\nanalyzers\/entity_extractor.py:382: request=f\"[entity_extraction] {prompt[:500]}...\",\nanalyzers\/entity_extractor.py:450: pipeline_step=\"entity_extract\",\nanalyzers\/statement_analyzer.py:18:from .entity_extractor import find_entity_by_name\nanalyzers\/document_analyzer.py:13:from .entity_extractor import extract_entities_anthropic, extract_entities_ollama, find_entity_by_name, store_entities\nrun_demo.py:18:from analyzers.entity_extractor import extract_entities_ollama, store_entities, _build_prompt_from_yaml\nrun_demo.py:124: prompt_data = db.get_prompt_by_use_case(\"entity_extraction\")\nsemantic_chunk\/pipeline.py:24: self.entity_extractor = EntityExtractor(self.llm)\nsemantic_chunk\/pipeline.py:49: entities = self.entity_extractor.extract(text)",
"numLines": 27
}
}