| source_references |
[{"documentId": "batch-31c0285e-ef14-4 [{"documentId": "batch-31c0285e-ef14-4c54-807e-7adeffb0dff2-356a3df1-e4e5-4c29-b3a6-ef32fbf3751d_chunk_16", "startIndex": 1096, "endIndex": 1105, "surroundingText": "\uf0b7 Visible \u2013 Consumers can locate the needed data.", "extractionConfidence": 0.85, "extractionMethod": "LLM_EXTRACTION", "extractedAt": "2025-12-03T15:24:25.969652Z"}, {"documentId": "batch-31c0285e-ef14-4c54-807e-7adeffb0dff2-356a3df1-e4e5-4c29-b3a6-ef32fbf3751d_chunk_16", "startIndex": 1150, "endIndex": 1159, "surroundingText": "\uf0b7 Accessible \u2013 Consumers can retrieve the data.", "extractionConfidence": 0.85, "extractionMethod": "LLM_EXTRACTION", "extractedAt": "2025-12-03T15:24:25.969668Z"}, {"documentId": "batch-31c0285e-ef14-4c54-807e-7adeffb0dff2-356a3df1-e4e5-4c29-b3a6-ef32fbf3751d_chunk_16", "startIndex": 1203, "endIndex": 1212, "surroundingText": "\uf0b7 Understandable \u2013 Consumers can find descriptions of data to recognize the content,", "extractionConfidence": 0.85, "extractionMethod": "LLM_EXTRACTION", "extractedAt": "2025-12-03T15:24:25.969685Z"}, {"documentId": "batch-31c0285e-ef14-4c54-807e-7adeffb0dff2-356a3df1-e4e5-4c29-b3a6-ef32fbf3751d_chunk_16", "startIndex": 1310, "endIndex": 1319, "surroundingText": "\uf0b7 Linked \u2013 Consumers can exploit complementary data elements through innate", "extractionConfidence": 0.85, "extractionMethod": "LLM_EXTRACTION", "extractedAt": "2025-12-03T15:24:25.969702Z"}, {"documentId": "batch-31c0285e-ef14-4c54-807e-7adeffb0dff2-356a3df1-e4e5-4c29-b3a6-ef32fbf3751d_chunk_16", "startIndex": 1408, "endIndex": 1417, "surroundingText": "\uf0b7 Trustworthy \u2013 Consumers can be confident in all aspects of data for decision-making.", "extractionConfidence": 0.85, "extractionMethod": "LLM_EXTRACTION", "extractedAt": "2025-12-03T15:24:25.969718Z"}]... |
| transformation_logs |
[{"id": "entity_transform_E-d847a68a46 [{"id": "entity_transform_E-d847a68a4627", "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-31c0285e-ef14-4c54-807e-7adeffb0dff2-356a3df1-e4e5-4c29-b3a6-ef32fbf3751d_chunk_16 using structured JSON schema", "modelName": "LLM_CLIENT", "startedAt": "2025-12-03T15:24:25.966223Z", "completedAt": "2025-12-03T15:24:25.966245Z"}]... |