id: https://nde.nl/ontology/hc/class/ExtractionMetadata name: extraction_metadata_class title: Extraction Metadata Class version: 1.0.0 prefixes: linkml: https://w3id.org/linkml/ hc: https://nde.nl/ontology/hc/ schema: http://schema.org/ prov: http://www.w3.org/ns/prov# dct: http://purl.org/dc/terms/ xsd: http://www.w3.org/2001/XMLSchema# imports: - linkml:types - ../enums/ProfileExtractionMethodEnum - ../metadata - ../slots/has_expense - ../slots/identified_by - ../slots/has_method - ../slots/has_score - ../slots/has_source - ../slots/has_url - ../slots/retrieved_by - ../slots/has_provenance - ../slots/retrieved_at # default_range: string classes: ExtractionMetadata: class_uri: prov:Activity description: "Provenance metadata for data extraction activities.\n\nRecords how, when, and by what agent data was extracted from \nexternal sources (LinkedIn, web scraping, APIs).\n\n**PROV-O Alignment**:\n- ExtractionMetadata IS a prov:Activity (the extraction process)\n- The extracted data IS the prov:Entity (output of the activity)\n- retrieved_by IS the prov:Agent (software/AI that performed extraction)\n- has_source/has_url IS prov:used (input to the activity)\n\n**Use Cases**:\n- LinkedIn profile extractions via Exa API\n- Web scraping provenance\n- Staff list parsing provenance\n- Connection network extraction\n\n**Example JSON Structure**:\n```json\n{\n \"extraction_metadata\": {\n \"has_source\": \"/path/to/source.json\",\n \"identified_by\": \"org_staff_0001_name\",\n \"retrieval_timestamp\": \"2025-12-12T22:00:00Z\",\n \"has_method\": \"exa_crawling_exa\",\n \"retrieved_by\": \"claude-opus-4.5\",\n \"has_url\": \"https://www.linkedin.com/in/...\"\ ,\n \"has_expense\": 0.001\n }\n}\n```\n" exact_mappings: - prov:Activity close_mappings: - schema:Action - dct:ProvenanceStatement slots: - has_expense - retrieved_by - retrieved_at - has_method - has_url - has_provenance - identified_by - has_source - has_score slot_usage: has_source: # range: string examples: - value: /data/custodian/person/affiliated/parsed/rijksmuseum_staff_20251210T155416Z.json identified_by: # range: string pattern: ^[a-z0-9-]+_staff_[a-z0-9-_]+$ examples: - value: rijksmuseum_staff_0042_jan_van_der_berg - value: exa_12345678-abcd-efgh-ijkl-mnopqrstuv retrieved_at: range: datetime required: true examples: - value: '2025-12-12T22:00:00Z' has_method: range: ProfileExtractionMethodEnum required: true examples: - value: exa_crawling_exa retrieved_by: # range: string examples: - value: claude-opus-4.5 - value: '' has_url: range: uri pattern: ^https://www\.linkedin\.com/in/[a-z0-9-]+/?$ examples: - value: https://www.linkedin.com/in/jan-van-der-berg-12345 has_expense: range: float minimum_value: 0.0 examples: - value: 0.001 - value: 0.0 has_provenance: range: LLMResponse required: false inlined: true examples: - value: "{\n \"content\": \"Extracted institution data...\",\n \"reasoning_content\": \"Analyzing the input for LinkML schema conformity...\",\n \"thinking_mode\": \"preserved\",\n \"clear_thinking\": false,\n \"model\": \"glm-4.7\",\n \"provider\": \"zai\",\n \"created\": \"2025-12-23T10:30:00Z\",\n \"prompt_tokens\": 150,\n \"completion_tokens\": 450,\n \"total_tokens\": 600,\n \"finish_reason\": \"stop\",\n \"cost_usd\": 0.0\n}\n" comments: - Every person entity file MUST have extraction_metadata - See AGENTS.md Rule 20 for required fields - retrieved_by should be 'claude-opus-4.5' for manual extraction - has_expense enables budget tracking for API-heavy extractions see_also: - https://www.w3.org/TR/prov-o/ - https://docs.exa.ai/ annotations: specificity_score: 0.1 specificity_rationale: Generic utility class/slot created during migration custodian_types: "['*']"