| source_references |
[{"documentId": "batch-ab1be436-e79b-4 [{"documentId": "batch-ab1be436-e79b-436b-8f65-7bbd5d03d519-c311ea18-6f02-461b-936e-65a4bc6e17c6_chunk_6", "startIndex": 1717, "endIndex": 1726, "surroundingText": "\uf0b7 Visible \u2013 Consumers can locate the needed data.", "extractionConfidence": 0.85, "extractionMethod": "LLM_EXTRACTION", "extractedAt": "2025-12-02T22:06:45.396296Z"}, {"documentId": "batch-ab1be436-e79b-436b-8f65-7bbd5d03d519-c311ea18-6f02-461b-936e-65a4bc6e17c6_chunk_6", "startIndex": 1771, "endIndex": 1780, "surroundingText": "\uf0b7 Accessible \u2013 Consumers can retrieve the data.", "extractionConfidence": 0.85, "extractionMethod": "LLM_EXTRACTION", "extractedAt": "2025-12-02T22:06:45.396313Z"}, {"documentId": "batch-ab1be436-e79b-436b-8f65-7bbd5d03d519-c311ea18-6f02-461b-936e-65a4bc6e17c6_chunk_6", "startIndex": 1824, "endIndex": 1833, "surroundingText": "\uf0b7 Understandable \u2013 Consumers can find descriptions of data to recognize the content,", "extractionConfidence": 0.85, "extractionMethod": "LLM_EXTRACTION", "extractedAt": "2025-12-02T22:06:45.396330Z"}, {"documentId": "batch-ab1be436-e79b-436b-8f65-7bbd5d03d519-c311ea18-6f02-461b-936e-65a4bc6e17c6_chunk_6", "startIndex": 1931, "endIndex": 1940, "surroundingText": "\uf0b7 Linked \u2013 Consumers can exploit complementary data elements through innate", "extractionConfidence": 0.85, "extractionMethod": "LLM_EXTRACTION", "extractedAt": "2025-12-02T22:06:45.396347Z"}, {"documentId": "batch-ab1be436-e79b-436b-8f65-7bbd5d03d519-c311ea18-6f02-461b-936e-65a4bc6e17c6_chunk_6", "startIndex": 2029, "endIndex": 2038, "surroundingText": "\uf0b7 Trustworthy \u2013 Consumers can be confident in all aspects of data for decision-making.", "extractionConfidence": 0.85, "extractionMethod": "LLM_EXTRACTION", "extractedAt": "2025-12-02T22:06:45.396363Z"}]... |
| transformation_logs |
[{"id": "entity_transform_E-c428c34550 [{"id": "entity_transform_E-c428c3455046", "stage": "TRANSFORMATION_STAGE_ENTITY_EXTRACTION", "method": "TRANSFORMATION_METHOD_LLM_PROMPT", "fromState": "raw_document_text", "toState": "extracted_entities", "finalConfidence": 0.85, "reasoning": "LLM-based entity extraction from document batch-ab1be436-e79b-436b-8f65-7bbd5d03d519-c311ea18-6f02-461b-936e-65a4bc6e17c6_chunk_6 using structured JSON schema", "modelName": "LLM_CLIENT", "startedAt": "2025-12-02T22:06:45.390476Z", "completedAt": "2025-12-02T22:06:45.390507Z"}]... |