Stored Transformation
Stored transformation detail
Inspect version history, edit inputs, and save a new version without overwriting prior records.
{ "id": .id, "type": .type, "address": .address, "category": .category, "dataProvider": .dataProvider, "description": .description, "location": .location, "name": .name, "source": .source, "status": .status, "subCategory": .subCategory }
{
"address": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"category": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"dataProvider": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"description": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"id": "building:hoteles.ayto-xlsx.141",
"location": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"name": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"status": {
"metadata": {},
"type": "string",
"value": "operational"
},
"subCategory": {
"metadata": {},
"type": "string",
"value": null
},
"type": "building"
}
Trace Details
{
"attempts": [
{
"attempt_number": 1,
"compile_ok": true,
"error_message": null,
"execution_ok": true,
"jq_expression": ".id",
"schema_valid": true,
"stage": "field",
"target_field": "id",
"used_hints": true
},
{
"attempt_number": 1,
"compile_ok": true,
"error_message": null,
"execution_ok": true,
"jq_expression": ".type",
"schema_valid": true,
"stage": "field",
"target_field": "type",
"used_hints": true
},
{
"attempt_number": 1,
"compile_ok": true,
"error_message": null,
"execution_ok": true,
"jq_expression": ".address",
"schema_valid": true,
"stage": "field",
"target_field": "address",
"used_hints": true
},
{
"attempt_number": 1,
"compile_ok": true,
"error_message": null,
"execution_ok": true,
"jq_expression": ".category",
"schema_valid": true,
"stage": "field",
"target_field": "category",
"used_hints": true
},
{
"attempt_number": 1,
"compile_ok": true,
"error_message": null,
"execution_ok": true,
"jq_expression": ".dataProvider",
"schema_valid": true,
"stage": "field",
"target_field": "dataProvider",
"used_hints": true
},
{
"attempt_number": 1,
"compile_ok": true,
"error_message": null,
"execution_ok": true,
"jq_expression": ".description",
"schema_valid": true,
"stage": "field",
"target_field": "description",
"used_hints": true
},
{
"attempt_number": 1,
"compile_ok": true,
"error_message": null,
"execution_ok": true,
"jq_expression": ".location",
"schema_valid": true,
"stage": "field",
"target_field": "location",
"used_hints": true
},
{
"attempt_number": 1,
"compile_ok": true,
"error_message": null,
"execution_ok": true,
"jq_expression": ".name",
"schema_valid": true,
"stage": "field",
"target_field": "name",
"used_hints": true
},
{
"attempt_number": 1,
"compile_ok": true,
"error_message": null,
"execution_ok": true,
"jq_expression": ".source",
"schema_valid": true,
"stage": "field",
"target_field": "source",
"used_hints": true
},
{
"attempt_number": 1,
"compile_ok": true,
"error_message": null,
"execution_ok": true,
"jq_expression": ".status",
"schema_valid": true,
"stage": "field",
"target_field": "status",
"used_hints": true
},
{
"attempt_number": 1,
"compile_ok": true,
"error_message": null,
"execution_ok": true,
"jq_expression": ".subCategory",
"schema_valid": true,
"stage": "field",
"target_field": "subCategory",
"used_hints": true
},
{
"attempt_number": 1,
"compile_ok": true,
"error_message": null,
"execution_ok": true,
"jq_expression": "{ \"id\": .id, \"type\": .type, \"address\": .address, \"category\": .category, \"dataProvider\": .dataProvider, \"description\": .description, \"location\": .location, \"name\": .name, \"source\": .source, \"status\": .status, \"subCategory\": .subCategory }",
"schema_valid": true,
"stage": "global",
"target_field": null,
"used_hints": true
}
],
"events": [
{
"payload": {
"field_name": "id",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"match_result": {
"candidate_source_path": "id",
"confidence": 0.99,
"identified": true,
"reasoning": "Direct match of field name and type"
},
"prompt_payload": {
"field_name": "id",
"field_schema": {
"type": "string"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"input_summary": {
"path_count": 43,
"paths": [
"address",
"address.metadata",
"address.type",
"address.value",
"category",
"category.metadata",
"category.type",
"category.value",
"category.value[0]",
"dataProvider",
"dataProvider.metadata",
"dataProvider.type",
"dataProvider.value",
"description",
"description.metadata",
"description.type",
"description.value",
"id",
"location",
"location.metadata",
"location.type",
"location.value",
"location.value.coordinates",
"location.value.coordinates[0]",
"location.value.coordinates[1]",
"location.value.type",
"name",
"name.metadata",
"name.type",
"name.value",
"source",
"source.metadata",
"source.type",
"source.value",
"status",
"status.metadata",
"status.type",
"status.value",
"subCategory",
"subCategory.metadata",
"subCategory.type",
"subCategory.value",
"type"
],
"root_type": "dict"
},
"output_schema": {
"properties": {
"address": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"category": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"dataProvider": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"description": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"id": {
"type": "string"
},
"location": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"properties": {
"coordinates": {
"items": {
"type": "number"
},
"type": "array"
},
"type": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"name": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"source": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"status": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"subCategory": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"id",
"type"
],
"type": "object"
},
"required": true,
"task": "match"
},
"response": "{\"identified\":true,\"candidate_source_path\":\"id\",\"reasoning\":\"Direct match of field name and type\",\"confidence\":0.99}",
"system_prompt": "You perform semantic field matching between a target schema field and source JSON paths. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like match, result, mapping, output, or data. Use exactly these keys: \"identified\", \"candidate_source_path\", \"reasoning\", \"confidence\". \"identified\" must be a JSON boolean. \"candidate_source_path\" must be a string path or null. \"reasoning\" must be a short string. \"confidence\" must be a JSON number between 0.0 and 1.0. If no reliable match exists, return identified=false, candidate_source_path=null, a brief reasoning string, and confidence=0.0. Example valid output: {\"identified\":true,\"candidate_source_path\":\"datetime\",\"reasoning\":\"The source field semantically matches the target date.\",\"confidence\":0.92}",
"used_hints": true
},
"stage": "semantic_match",
"timestamp": "2026-05-18T15:52:58.645999+00:00"
},
{
"payload": {
"field_name": "type",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"match_result": {
"candidate_source_path": "type",
"confidence": 0.99,
"identified": true,
"reasoning": "Direct match of field name and type"
},
"prompt_payload": {
"field_name": "type",
"field_schema": {
"type": "string"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"input_summary": {
"path_count": 43,
"paths": [
"address",
"address.metadata",
"address.type",
"address.value",
"category",
"category.metadata",
"category.type",
"category.value",
"category.value[0]",
"dataProvider",
"dataProvider.metadata",
"dataProvider.type",
"dataProvider.value",
"description",
"description.metadata",
"description.type",
"description.value",
"id",
"location",
"location.metadata",
"location.type",
"location.value",
"location.value.coordinates",
"location.value.coordinates[0]",
"location.value.coordinates[1]",
"location.value.type",
"name",
"name.metadata",
"name.type",
"name.value",
"source",
"source.metadata",
"source.type",
"source.value",
"status",
"status.metadata",
"status.type",
"status.value",
"subCategory",
"subCategory.metadata",
"subCategory.type",
"subCategory.value",
"type"
],
"root_type": "dict"
},
"output_schema": {
"properties": {
"address": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"category": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"dataProvider": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"description": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"id": {
"type": "string"
},
"location": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"properties": {
"coordinates": {
"items": {
"type": "number"
},
"type": "array"
},
"type": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"name": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"source": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"status": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"subCategory": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"id",
"type"
],
"type": "object"
},
"required": true,
"task": "match"
},
"response": "{\"identified\":true,\"candidate_source_path\":\"type\",\"reasoning\":\"Direct match of field name and type\",\"confidence\":0.99}",
"system_prompt": "You perform semantic field matching between a target schema field and source JSON paths. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like match, result, mapping, output, or data. Use exactly these keys: \"identified\", \"candidate_source_path\", \"reasoning\", \"confidence\". \"identified\" must be a JSON boolean. \"candidate_source_path\" must be a string path or null. \"reasoning\" must be a short string. \"confidence\" must be a JSON number between 0.0 and 1.0. If no reliable match exists, return identified=false, candidate_source_path=null, a brief reasoning string, and confidence=0.0. Example valid output: {\"identified\":true,\"candidate_source_path\":\"datetime\",\"reasoning\":\"The source field semantically matches the target date.\",\"confidence\":0.92}",
"used_hints": true
},
"stage": "semantic_match",
"timestamp": "2026-05-18T15:53:00.556367+00:00"
},
{
"payload": {
"field_name": "address",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"match_result": {
"candidate_source_path": "address",
"confidence": 0.99,
"identified": true,
"reasoning": "Direct match of field name and structure."
},
"prompt_payload": {
"field_name": "address",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"input_summary": {
"path_count": 43,
"paths": [
"address",
"address.metadata",
"address.type",
"address.value",
"category",
"category.metadata",
"category.type",
"category.value",
"category.value[0]",
"dataProvider",
"dataProvider.metadata",
"dataProvider.type",
"dataProvider.value",
"description",
"description.metadata",
"description.type",
"description.value",
"id",
"location",
"location.metadata",
"location.type",
"location.value",
"location.value.coordinates",
"location.value.coordinates[0]",
"location.value.coordinates[1]",
"location.value.type",
"name",
"name.metadata",
"name.type",
"name.value",
"source",
"source.metadata",
"source.type",
"source.value",
"status",
"status.metadata",
"status.type",
"status.value",
"subCategory",
"subCategory.metadata",
"subCategory.type",
"subCategory.value",
"type"
],
"root_type": "dict"
},
"output_schema": {
"properties": {
"address": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"category": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"dataProvider": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"description": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"id": {
"type": "string"
},
"location": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"properties": {
"coordinates": {
"items": {
"type": "number"
},
"type": "array"
},
"type": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"name": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"source": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"status": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"subCategory": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"id",
"type"
],
"type": "object"
},
"required": false,
"task": "match"
},
"response": "{\"identified\":true,\"candidate_source_path\":\"address\",\"reasoning\":\"Direct match of field name and structure.\",\"confidence\":0.99}",
"system_prompt": "You perform semantic field matching between a target schema field and source JSON paths. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like match, result, mapping, output, or data. Use exactly these keys: \"identified\", \"candidate_source_path\", \"reasoning\", \"confidence\". \"identified\" must be a JSON boolean. \"candidate_source_path\" must be a string path or null. \"reasoning\" must be a short string. \"confidence\" must be a JSON number between 0.0 and 1.0. If no reliable match exists, return identified=false, candidate_source_path=null, a brief reasoning string, and confidence=0.0. Example valid output: {\"identified\":true,\"candidate_source_path\":\"datetime\",\"reasoning\":\"The source field semantically matches the target date.\",\"confidence\":0.92}",
"used_hints": true
},
"stage": "semantic_match",
"timestamp": "2026-05-18T15:53:02.880304+00:00"
},
{
"payload": {
"field_name": "category",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"match_result": {
"candidate_source_path": "category",
"confidence": 0.99,
"identified": true,
"reasoning": "Direct match of field name and structure."
},
"prompt_payload": {
"field_name": "category",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"input_summary": {
"path_count": 43,
"paths": [
"address",
"address.metadata",
"address.type",
"address.value",
"category",
"category.metadata",
"category.type",
"category.value",
"category.value[0]",
"dataProvider",
"dataProvider.metadata",
"dataProvider.type",
"dataProvider.value",
"description",
"description.metadata",
"description.type",
"description.value",
"id",
"location",
"location.metadata",
"location.type",
"location.value",
"location.value.coordinates",
"location.value.coordinates[0]",
"location.value.coordinates[1]",
"location.value.type",
"name",
"name.metadata",
"name.type",
"name.value",
"source",
"source.metadata",
"source.type",
"source.value",
"status",
"status.metadata",
"status.type",
"status.value",
"subCategory",
"subCategory.metadata",
"subCategory.type",
"subCategory.value",
"type"
],
"root_type": "dict"
},
"output_schema": {
"properties": {
"address": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"category": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"dataProvider": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"description": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"id": {
"type": "string"
},
"location": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"properties": {
"coordinates": {
"items": {
"type": "number"
},
"type": "array"
},
"type": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"name": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"source": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"status": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"subCategory": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"id",
"type"
],
"type": "object"
},
"required": false,
"task": "match"
},
"response": "{\"identified\":true,\"candidate_source_path\":\"category\",\"reasoning\":\"Direct match of field name and structure.\",\"confidence\":0.99}",
"system_prompt": "You perform semantic field matching between a target schema field and source JSON paths. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like match, result, mapping, output, or data. Use exactly these keys: \"identified\", \"candidate_source_path\", \"reasoning\", \"confidence\". \"identified\" must be a JSON boolean. \"candidate_source_path\" must be a string path or null. \"reasoning\" must be a short string. \"confidence\" must be a JSON number between 0.0 and 1.0. If no reliable match exists, return identified=false, candidate_source_path=null, a brief reasoning string, and confidence=0.0. Example valid output: {\"identified\":true,\"candidate_source_path\":\"datetime\",\"reasoning\":\"The source field semantically matches the target date.\",\"confidence\":0.92}",
"used_hints": true
},
"stage": "semantic_match",
"timestamp": "2026-05-18T15:53:05.521497+00:00"
},
{
"payload": {
"field_name": "dataProvider",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"match_result": {
"candidate_source_path": "dataProvider",
"confidence": 0.99,
"identified": true,
"reasoning": "Direct match of field name and structure."
},
"prompt_payload": {
"field_name": "dataProvider",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"input_summary": {
"path_count": 43,
"paths": [
"address",
"address.metadata",
"address.type",
"address.value",
"category",
"category.metadata",
"category.type",
"category.value",
"category.value[0]",
"dataProvider",
"dataProvider.metadata",
"dataProvider.type",
"dataProvider.value",
"description",
"description.metadata",
"description.type",
"description.value",
"id",
"location",
"location.metadata",
"location.type",
"location.value",
"location.value.coordinates",
"location.value.coordinates[0]",
"location.value.coordinates[1]",
"location.value.type",
"name",
"name.metadata",
"name.type",
"name.value",
"source",
"source.metadata",
"source.type",
"source.value",
"status",
"status.metadata",
"status.type",
"status.value",
"subCategory",
"subCategory.metadata",
"subCategory.type",
"subCategory.value",
"type"
],
"root_type": "dict"
},
"output_schema": {
"properties": {
"address": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"category": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"dataProvider": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"description": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"id": {
"type": "string"
},
"location": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"properties": {
"coordinates": {
"items": {
"type": "number"
},
"type": "array"
},
"type": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"name": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"source": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"status": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"subCategory": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"id",
"type"
],
"type": "object"
},
"required": false,
"task": "match"
},
"response": "{\"identified\":true,\"candidate_source_path\":\"dataProvider\",\"reasoning\":\"Direct match of field name and structure.\",\"confidence\":0.99}",
"system_prompt": "You perform semantic field matching between a target schema field and source JSON paths. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like match, result, mapping, output, or data. Use exactly these keys: \"identified\", \"candidate_source_path\", \"reasoning\", \"confidence\". \"identified\" must be a JSON boolean. \"candidate_source_path\" must be a string path or null. \"reasoning\" must be a short string. \"confidence\" must be a JSON number between 0.0 and 1.0. If no reliable match exists, return identified=false, candidate_source_path=null, a brief reasoning string, and confidence=0.0. Example valid output: {\"identified\":true,\"candidate_source_path\":\"datetime\",\"reasoning\":\"The source field semantically matches the target date.\",\"confidence\":0.92}",
"used_hints": true
},
"stage": "semantic_match",
"timestamp": "2026-05-18T15:53:07.868873+00:00"
},
{
"payload": {
"field_name": "description",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"match_result": {
"candidate_source_path": "description",
"confidence": 0.99,
"identified": true,
"reasoning": "Direct match of field name and structure."
},
"prompt_payload": {
"field_name": "description",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"input_summary": {
"path_count": 43,
"paths": [
"address",
"address.metadata",
"address.type",
"address.value",
"category",
"category.metadata",
"category.type",
"category.value",
"category.value[0]",
"dataProvider",
"dataProvider.metadata",
"dataProvider.type",
"dataProvider.value",
"description",
"description.metadata",
"description.type",
"description.value",
"id",
"location",
"location.metadata",
"location.type",
"location.value",
"location.value.coordinates",
"location.value.coordinates[0]",
"location.value.coordinates[1]",
"location.value.type",
"name",
"name.metadata",
"name.type",
"name.value",
"source",
"source.metadata",
"source.type",
"source.value",
"status",
"status.metadata",
"status.type",
"status.value",
"subCategory",
"subCategory.metadata",
"subCategory.type",
"subCategory.value",
"type"
],
"root_type": "dict"
},
"output_schema": {
"properties": {
"address": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"category": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"dataProvider": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"description": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"id": {
"type": "string"
},
"location": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"properties": {
"coordinates": {
"items": {
"type": "number"
},
"type": "array"
},
"type": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"name": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"source": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"status": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"subCategory": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"id",
"type"
],
"type": "object"
},
"required": false,
"task": "match"
},
"response": "{\"identified\":true,\"candidate_source_path\":\"description\",\"reasoning\":\"Direct match of field name and structure.\",\"confidence\":0.99}",
"system_prompt": "You perform semantic field matching between a target schema field and source JSON paths. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like match, result, mapping, output, or data. Use exactly these keys: \"identified\", \"candidate_source_path\", \"reasoning\", \"confidence\". \"identified\" must be a JSON boolean. \"candidate_source_path\" must be a string path or null. \"reasoning\" must be a short string. \"confidence\" must be a JSON number between 0.0 and 1.0. If no reliable match exists, return identified=false, candidate_source_path=null, a brief reasoning string, and confidence=0.0. Example valid output: {\"identified\":true,\"candidate_source_path\":\"datetime\",\"reasoning\":\"The source field semantically matches the target date.\",\"confidence\":0.92}",
"used_hints": true
},
"stage": "semantic_match",
"timestamp": "2026-05-18T15:53:10.198867+00:00"
},
{
"payload": {
"field_name": "location",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"match_result": {
"candidate_source_path": "location",
"confidence": 0.99,
"identified": true,
"reasoning": "Direct match of field name and structure."
},
"prompt_payload": {
"field_name": "location",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"properties": {
"coordinates": {
"items": {
"type": "number"
},
"type": "array"
},
"type": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"input_summary": {
"path_count": 43,
"paths": [
"address",
"address.metadata",
"address.type",
"address.value",
"category",
"category.metadata",
"category.type",
"category.value",
"category.value[0]",
"dataProvider",
"dataProvider.metadata",
"dataProvider.type",
"dataProvider.value",
"description",
"description.metadata",
"description.type",
"description.value",
"id",
"location",
"location.metadata",
"location.type",
"location.value",
"location.value.coordinates",
"location.value.coordinates[0]",
"location.value.coordinates[1]",
"location.value.type",
"name",
"name.metadata",
"name.type",
"name.value",
"source",
"source.metadata",
"source.type",
"source.value",
"status",
"status.metadata",
"status.type",
"status.value",
"subCategory",
"subCategory.metadata",
"subCategory.type",
"subCategory.value",
"type"
],
"root_type": "dict"
},
"output_schema": {
"properties": {
"address": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"category": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"dataProvider": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"description": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"id": {
"type": "string"
},
"location": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"properties": {
"coordinates": {
"items": {
"type": "number"
},
"type": "array"
},
"type": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"name": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"source": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"status": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"subCategory": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"id",
"type"
],
"type": "object"
},
"required": false,
"task": "match"
},
"response": "{\"identified\":true,\"candidate_source_path\":\"location\",\"reasoning\":\"Direct match of field name and structure.\",\"confidence\":0.99}",
"system_prompt": "You perform semantic field matching between a target schema field and source JSON paths. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like match, result, mapping, output, or data. Use exactly these keys: \"identified\", \"candidate_source_path\", \"reasoning\", \"confidence\". \"identified\" must be a JSON boolean. \"candidate_source_path\" must be a string path or null. \"reasoning\" must be a short string. \"confidence\" must be a JSON number between 0.0 and 1.0. If no reliable match exists, return identified=false, candidate_source_path=null, a brief reasoning string, and confidence=0.0. Example valid output: {\"identified\":true,\"candidate_source_path\":\"datetime\",\"reasoning\":\"The source field semantically matches the target date.\",\"confidence\":0.92}",
"used_hints": true
},
"stage": "semantic_match",
"timestamp": "2026-05-18T15:53:12.579781+00:00"
},
{
"payload": {
"field_name": "name",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"match_result": {
"candidate_source_path": "name",
"confidence": 0.99,
"identified": true,
"reasoning": "Direct match of field name in source paths."
},
"prompt_payload": {
"field_name": "name",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"input_summary": {
"path_count": 43,
"paths": [
"address",
"address.metadata",
"address.type",
"address.value",
"category",
"category.metadata",
"category.type",
"category.value",
"category.value[0]",
"dataProvider",
"dataProvider.metadata",
"dataProvider.type",
"dataProvider.value",
"description",
"description.metadata",
"description.type",
"description.value",
"id",
"location",
"location.metadata",
"location.type",
"location.value",
"location.value.coordinates",
"location.value.coordinates[0]",
"location.value.coordinates[1]",
"location.value.type",
"name",
"name.metadata",
"name.type",
"name.value",
"source",
"source.metadata",
"source.type",
"source.value",
"status",
"status.metadata",
"status.type",
"status.value",
"subCategory",
"subCategory.metadata",
"subCategory.type",
"subCategory.value",
"type"
],
"root_type": "dict"
},
"output_schema": {
"properties": {
"address": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"category": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"dataProvider": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"description": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"id": {
"type": "string"
},
"location": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"properties": {
"coordinates": {
"items": {
"type": "number"
},
"type": "array"
},
"type": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"name": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"source": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"status": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"subCategory": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"id",
"type"
],
"type": "object"
},
"required": false,
"task": "match"
},
"response": "{\"identified\":true,\"candidate_source_path\":\"name\",\"reasoning\":\"Direct match of field name in source paths.\",\"confidence\":0.99}",
"system_prompt": "You perform semantic field matching between a target schema field and source JSON paths. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like match, result, mapping, output, or data. Use exactly these keys: \"identified\", \"candidate_source_path\", \"reasoning\", \"confidence\". \"identified\" must be a JSON boolean. \"candidate_source_path\" must be a string path or null. \"reasoning\" must be a short string. \"confidence\" must be a JSON number between 0.0 and 1.0. If no reliable match exists, return identified=false, candidate_source_path=null, a brief reasoning string, and confidence=0.0. Example valid output: {\"identified\":true,\"candidate_source_path\":\"datetime\",\"reasoning\":\"The source field semantically matches the target date.\",\"confidence\":0.92}",
"used_hints": true
},
"stage": "semantic_match",
"timestamp": "2026-05-18T15:53:14.717987+00:00"
},
{
"payload": {
"field_name": "source",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"match_result": {
"candidate_source_path": "source",
"confidence": 0.99,
"identified": true,
"reasoning": "Direct match of field name and structure."
},
"prompt_payload": {
"field_name": "source",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"input_summary": {
"path_count": 43,
"paths": [
"address",
"address.metadata",
"address.type",
"address.value",
"category",
"category.metadata",
"category.type",
"category.value",
"category.value[0]",
"dataProvider",
"dataProvider.metadata",
"dataProvider.type",
"dataProvider.value",
"description",
"description.metadata",
"description.type",
"description.value",
"id",
"location",
"location.metadata",
"location.type",
"location.value",
"location.value.coordinates",
"location.value.coordinates[0]",
"location.value.coordinates[1]",
"location.value.type",
"name",
"name.metadata",
"name.type",
"name.value",
"source",
"source.metadata",
"source.type",
"source.value",
"status",
"status.metadata",
"status.type",
"status.value",
"subCategory",
"subCategory.metadata",
"subCategory.type",
"subCategory.value",
"type"
],
"root_type": "dict"
},
"output_schema": {
"properties": {
"address": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"category": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"dataProvider": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"description": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"id": {
"type": "string"
},
"location": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"properties": {
"coordinates": {
"items": {
"type": "number"
},
"type": "array"
},
"type": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"name": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"source": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"status": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"subCategory": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"id",
"type"
],
"type": "object"
},
"required": false,
"task": "match"
},
"response": "{\"identified\":true,\"candidate_source_path\":\"source\",\"reasoning\":\"Direct match of field name and structure.\",\"confidence\":0.99}",
"system_prompt": "You perform semantic field matching between a target schema field and source JSON paths. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like match, result, mapping, output, or data. Use exactly these keys: \"identified\", \"candidate_source_path\", \"reasoning\", \"confidence\". \"identified\" must be a JSON boolean. \"candidate_source_path\" must be a string path or null. \"reasoning\" must be a short string. \"confidence\" must be a JSON number between 0.0 and 1.0. If no reliable match exists, return identified=false, candidate_source_path=null, a brief reasoning string, and confidence=0.0. Example valid output: {\"identified\":true,\"candidate_source_path\":\"datetime\",\"reasoning\":\"The source field semantically matches the target date.\",\"confidence\":0.92}",
"used_hints": true
},
"stage": "semantic_match",
"timestamp": "2026-05-18T15:53:17.024184+00:00"
},
{
"payload": {
"field_name": "status",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"match_result": {
"candidate_source_path": "status",
"confidence": 0.99,
"identified": true,
"reasoning": "Direct match of field name and structure."
},
"prompt_payload": {
"field_name": "status",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"input_summary": {
"path_count": 43,
"paths": [
"address",
"address.metadata",
"address.type",
"address.value",
"category",
"category.metadata",
"category.type",
"category.value",
"category.value[0]",
"dataProvider",
"dataProvider.metadata",
"dataProvider.type",
"dataProvider.value",
"description",
"description.metadata",
"description.type",
"description.value",
"id",
"location",
"location.metadata",
"location.type",
"location.value",
"location.value.coordinates",
"location.value.coordinates[0]",
"location.value.coordinates[1]",
"location.value.type",
"name",
"name.metadata",
"name.type",
"name.value",
"source",
"source.metadata",
"source.type",
"source.value",
"status",
"status.metadata",
"status.type",
"status.value",
"subCategory",
"subCategory.metadata",
"subCategory.type",
"subCategory.value",
"type"
],
"root_type": "dict"
},
"output_schema": {
"properties": {
"address": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"category": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"dataProvider": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"description": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"id": {
"type": "string"
},
"location": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"properties": {
"coordinates": {
"items": {
"type": "number"
},
"type": "array"
},
"type": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"name": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"source": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"status": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"subCategory": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"id",
"type"
],
"type": "object"
},
"required": false,
"task": "match"
},
"response": "{\"identified\":true,\"candidate_source_path\":\"status\",\"reasoning\":\"Direct match of field name and structure.\",\"confidence\":0.99}",
"system_prompt": "You perform semantic field matching between a target schema field and source JSON paths. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like match, result, mapping, output, or data. Use exactly these keys: \"identified\", \"candidate_source_path\", \"reasoning\", \"confidence\". \"identified\" must be a JSON boolean. \"candidate_source_path\" must be a string path or null. \"reasoning\" must be a short string. \"confidence\" must be a JSON number between 0.0 and 1.0. If no reliable match exists, return identified=false, candidate_source_path=null, a brief reasoning string, and confidence=0.0. Example valid output: {\"identified\":true,\"candidate_source_path\":\"datetime\",\"reasoning\":\"The source field semantically matches the target date.\",\"confidence\":0.92}",
"used_hints": true
},
"stage": "semantic_match",
"timestamp": "2026-05-18T15:53:19.369629+00:00"
},
{
"payload": {
"field_name": "subCategory",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"match_result": {
"candidate_source_path": "subCategory",
"confidence": 0.99,
"identified": true,
"reasoning": "Direct match of field name and structure."
},
"prompt_payload": {
"field_name": "subCategory",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"input_summary": {
"path_count": 43,
"paths": [
"address",
"address.metadata",
"address.type",
"address.value",
"category",
"category.metadata",
"category.type",
"category.value",
"category.value[0]",
"dataProvider",
"dataProvider.metadata",
"dataProvider.type",
"dataProvider.value",
"description",
"description.metadata",
"description.type",
"description.value",
"id",
"location",
"location.metadata",
"location.type",
"location.value",
"location.value.coordinates",
"location.value.coordinates[0]",
"location.value.coordinates[1]",
"location.value.type",
"name",
"name.metadata",
"name.type",
"name.value",
"source",
"source.metadata",
"source.type",
"source.value",
"status",
"status.metadata",
"status.type",
"status.value",
"subCategory",
"subCategory.metadata",
"subCategory.type",
"subCategory.value",
"type"
],
"root_type": "dict"
},
"output_schema": {
"properties": {
"address": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"category": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"dataProvider": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"description": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"id": {
"type": "string"
},
"location": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"properties": {
"coordinates": {
"items": {
"type": "number"
},
"type": "array"
},
"type": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"name": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"source": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"status": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"subCategory": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"id",
"type"
],
"type": "object"
},
"required": false,
"task": "match"
},
"response": "{\"identified\":true,\"candidate_source_path\":\"subCategory\",\"reasoning\":\"Direct match of field name and structure.\",\"confidence\":0.99}",
"system_prompt": "You perform semantic field matching between a target schema field and source JSON paths. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like match, result, mapping, output, or data. Use exactly these keys: \"identified\", \"candidate_source_path\", \"reasoning\", \"confidence\". \"identified\" must be a JSON boolean. \"candidate_source_path\" must be a string path or null. \"reasoning\" must be a short string. \"confidence\" must be a JSON number between 0.0 and 1.0. If no reliable match exists, return identified=false, candidate_source_path=null, a brief reasoning string, and confidence=0.0. Example valid output: {\"identified\":true,\"candidate_source_path\":\"datetime\",\"reasoning\":\"The source field semantically matches the target date.\",\"confidence\":0.92}",
"used_hints": true
},
"stage": "semantic_match",
"timestamp": "2026-05-18T15:53:21.859814+00:00"
},
{
"payload": {
"field_name": "id",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"jq_expression": ".id",
"prompt_payload": {
"candidate_source_path": "id",
"field_name": "id",
"field_schema": {
"type": "string"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"source_fragment": "building:hoteles.ayto-xlsx.141",
"source_json": {
"address": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"category": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"dataProvider": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"description": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"id": "building:hoteles.ayto-xlsx.141",
"location": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"name": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"status": {
"metadata": {},
"type": "string",
"value": "operational"
},
"subCategory": {
"metadata": {},
"type": "string",
"value": null
},
"type": "building"
},
"task": "synthesize"
},
"response": "{\"jq_expression\":\".id\"}",
"system_prompt": "You generate a jq expression for one target field. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like result, output, data, or expression. Use exactly this output schema: {\"jq_expression\": string}. \"jq_expression\" must be a JSON string containing only the jq expression for the target field. Use candidate_source_path as the primary source location, verify it against source_json, and use source_fragment as the focused local value. Do not return explanations or extra keys. Example valid output: {\"jq_expression\":\".datetime\"}",
"used_hints": true
},
"stage": "jq_synthesis",
"timestamp": "2026-05-18T15:53:25.256786+00:00"
},
{
"payload": {
"field_name": "type",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"jq_expression": ".type",
"prompt_payload": {
"candidate_source_path": "type",
"field_name": "type",
"field_schema": {
"type": "string"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"source_fragment": "building",
"source_json": {
"address": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"category": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"dataProvider": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"description": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"id": "building:hoteles.ayto-xlsx.141",
"location": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"name": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"status": {
"metadata": {},
"type": "string",
"value": "operational"
},
"subCategory": {
"metadata": {},
"type": "string",
"value": null
},
"type": "building"
},
"task": "synthesize"
},
"response": "{\"jq_expression\":\".type\"}",
"system_prompt": "You generate a jq expression for one target field. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like result, output, data, or expression. Use exactly this output schema: {\"jq_expression\": string}. \"jq_expression\" must be a JSON string containing only the jq expression for the target field. Use candidate_source_path as the primary source location, verify it against source_json, and use source_fragment as the focused local value. Do not return explanations or extra keys. Example valid output: {\"jq_expression\":\".datetime\"}",
"used_hints": true
},
"stage": "jq_synthesis",
"timestamp": "2026-05-18T15:53:29.088747+00:00"
},
{
"payload": {
"field_name": "address",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"jq_expression": ".address",
"prompt_payload": {
"candidate_source_path": "address",
"field_name": "address",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"source_fragment": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"source_json": {
"address": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"category": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"dataProvider": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"description": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"id": "building:hoteles.ayto-xlsx.141",
"location": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"name": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"status": {
"metadata": {},
"type": "string",
"value": "operational"
},
"subCategory": {
"metadata": {},
"type": "string",
"value": null
},
"type": "building"
},
"task": "synthesize"
},
"response": "{\"jq_expression\":\".address\"}",
"system_prompt": "You generate a jq expression for one target field. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like result, output, data, or expression. Use exactly this output schema: {\"jq_expression\": string}. \"jq_expression\" must be a JSON string containing only the jq expression for the target field. Use candidate_source_path as the primary source location, verify it against source_json, and use source_fragment as the focused local value. Do not return explanations or extra keys. Example valid output: {\"jq_expression\":\".datetime\"}",
"used_hints": true
},
"stage": "jq_synthesis",
"timestamp": "2026-05-18T15:53:33.224165+00:00"
},
{
"payload": {
"field_name": "category",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"jq_expression": ".category",
"prompt_payload": {
"candidate_source_path": "category",
"field_name": "category",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"source_fragment": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"source_json": {
"address": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"category": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"dataProvider": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"description": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"id": "building:hoteles.ayto-xlsx.141",
"location": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"name": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"status": {
"metadata": {},
"type": "string",
"value": "operational"
},
"subCategory": {
"metadata": {},
"type": "string",
"value": null
},
"type": "building"
},
"task": "synthesize"
},
"response": "{\"jq_expression\":\".category\"}",
"system_prompt": "You generate a jq expression for one target field. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like result, output, data, or expression. Use exactly this output schema: {\"jq_expression\": string}. \"jq_expression\" must be a JSON string containing only the jq expression for the target field. Use candidate_source_path as the primary source location, verify it against source_json, and use source_fragment as the focused local value. Do not return explanations or extra keys. Example valid output: {\"jq_expression\":\".datetime\"}",
"used_hints": true
},
"stage": "jq_synthesis",
"timestamp": "2026-05-18T15:53:37.163120+00:00"
},
{
"payload": {
"field_name": "dataProvider",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"jq_expression": ".dataProvider",
"prompt_payload": {
"candidate_source_path": "dataProvider",
"field_name": "dataProvider",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"source_fragment": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"source_json": {
"address": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"category": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"dataProvider": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"description": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"id": "building:hoteles.ayto-xlsx.141",
"location": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"name": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"status": {
"metadata": {},
"type": "string",
"value": "operational"
},
"subCategory": {
"metadata": {},
"type": "string",
"value": null
},
"type": "building"
},
"task": "synthesize"
},
"response": "{\"jq_expression\":\".dataProvider\"}",
"system_prompt": "You generate a jq expression for one target field. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like result, output, data, or expression. Use exactly this output schema: {\"jq_expression\": string}. \"jq_expression\" must be a JSON string containing only the jq expression for the target field. Use candidate_source_path as the primary source location, verify it against source_json, and use source_fragment as the focused local value. Do not return explanations or extra keys. Example valid output: {\"jq_expression\":\".datetime\"}",
"used_hints": true
},
"stage": "jq_synthesis",
"timestamp": "2026-05-18T15:53:41.930561+00:00"
},
{
"payload": {
"field_name": "description",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"jq_expression": ".description",
"prompt_payload": {
"candidate_source_path": "description",
"field_name": "description",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"source_fragment": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source_json": {
"address": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"category": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"dataProvider": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"description": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"id": "building:hoteles.ayto-xlsx.141",
"location": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"name": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"status": {
"metadata": {},
"type": "string",
"value": "operational"
},
"subCategory": {
"metadata": {},
"type": "string",
"value": null
},
"type": "building"
},
"task": "synthesize"
},
"response": "{\"jq_expression\":\".description\"}",
"system_prompt": "You generate a jq expression for one target field. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like result, output, data, or expression. Use exactly this output schema: {\"jq_expression\": string}. \"jq_expression\" must be a JSON string containing only the jq expression for the target field. Use candidate_source_path as the primary source location, verify it against source_json, and use source_fragment as the focused local value. Do not return explanations or extra keys. Example valid output: {\"jq_expression\":\".datetime\"}",
"used_hints": true
},
"stage": "jq_synthesis",
"timestamp": "2026-05-18T15:53:46.700485+00:00"
},
{
"payload": {
"field_name": "location",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"jq_expression": ".location",
"prompt_payload": {
"candidate_source_path": "location",
"field_name": "location",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"properties": {
"coordinates": {
"items": {
"type": "number"
},
"type": "array"
},
"type": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"source_fragment": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"source_json": {
"address": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"category": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"dataProvider": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"description": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"id": "building:hoteles.ayto-xlsx.141",
"location": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"name": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"status": {
"metadata": {},
"type": "string",
"value": "operational"
},
"subCategory": {
"metadata": {},
"type": "string",
"value": null
},
"type": "building"
},
"task": "synthesize"
},
"response": "{\"jq_expression\":\".location\"}",
"system_prompt": "You generate a jq expression for one target field. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like result, output, data, or expression. Use exactly this output schema: {\"jq_expression\": string}. \"jq_expression\" must be a JSON string containing only the jq expression for the target field. Use candidate_source_path as the primary source location, verify it against source_json, and use source_fragment as the focused local value. Do not return explanations or extra keys. Example valid output: {\"jq_expression\":\".datetime\"}",
"used_hints": true
},
"stage": "jq_synthesis",
"timestamp": "2026-05-18T15:53:50.832172+00:00"
},
{
"payload": {
"field_name": "name",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"jq_expression": ".name",
"prompt_payload": {
"candidate_source_path": "name",
"field_name": "name",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"source_fragment": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source_json": {
"address": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"category": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"dataProvider": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"description": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"id": "building:hoteles.ayto-xlsx.141",
"location": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"name": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"status": {
"metadata": {},
"type": "string",
"value": "operational"
},
"subCategory": {
"metadata": {},
"type": "string",
"value": null
},
"type": "building"
},
"task": "synthesize"
},
"response": "{\"jq_expression\":\".name\"}",
"system_prompt": "You generate a jq expression for one target field. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like result, output, data, or expression. Use exactly this output schema: {\"jq_expression\": string}. \"jq_expression\" must be a JSON string containing only the jq expression for the target field. Use candidate_source_path as the primary source location, verify it against source_json, and use source_fragment as the focused local value. Do not return explanations or extra keys. Example valid output: {\"jq_expression\":\".datetime\"}",
"used_hints": true
},
"stage": "jq_synthesis",
"timestamp": "2026-05-18T15:53:56.131257+00:00"
},
{
"payload": {
"field_name": "source",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"jq_expression": ".source",
"prompt_payload": {
"candidate_source_path": "source",
"field_name": "source",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"source_fragment": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"source_json": {
"address": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"category": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"dataProvider": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"description": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"id": "building:hoteles.ayto-xlsx.141",
"location": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"name": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"status": {
"metadata": {},
"type": "string",
"value": "operational"
},
"subCategory": {
"metadata": {},
"type": "string",
"value": null
},
"type": "building"
},
"task": "synthesize"
},
"response": "{\"jq_expression\":\".source\"}",
"system_prompt": "You generate a jq expression for one target field. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like result, output, data, or expression. Use exactly this output schema: {\"jq_expression\": string}. \"jq_expression\" must be a JSON string containing only the jq expression for the target field. Use candidate_source_path as the primary source location, verify it against source_json, and use source_fragment as the focused local value. Do not return explanations or extra keys. Example valid output: {\"jq_expression\":\".datetime\"}",
"used_hints": true
},
"stage": "jq_synthesis",
"timestamp": "2026-05-18T15:54:00.158177+00:00"
},
{
"payload": {
"field_name": "status",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"jq_expression": ".status",
"prompt_payload": {
"candidate_source_path": "status",
"field_name": "status",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"source_fragment": {
"metadata": {},
"type": "string",
"value": "operational"
},
"source_json": {
"address": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"category": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"dataProvider": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"description": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"id": "building:hoteles.ayto-xlsx.141",
"location": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"name": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"status": {
"metadata": {},
"type": "string",
"value": "operational"
},
"subCategory": {
"metadata": {},
"type": "string",
"value": null
},
"type": "building"
},
"task": "synthesize"
},
"response": "{\"jq_expression\":\".status\"}",
"system_prompt": "You generate a jq expression for one target field. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like result, output, data, or expression. Use exactly this output schema: {\"jq_expression\": string}. \"jq_expression\" must be a JSON string containing only the jq expression for the target field. Use candidate_source_path as the primary source location, verify it against source_json, and use source_fragment as the focused local value. Do not return explanations or extra keys. Example valid output: {\"jq_expression\":\".datetime\"}",
"used_hints": true
},
"stage": "jq_synthesis",
"timestamp": "2026-05-18T15:54:04.373065+00:00"
},
{
"payload": {
"field_name": "subCategory",
"hint_hash": "8cedb7ca398fb53023c683009fd9ad16b97e5658f811ee98da40bc8b89cd67f9",
"jq_expression": ".subCategory",
"prompt_payload": {
"candidate_source_path": "subCategory",
"field_name": "subCategory",
"field_schema": {
"properties": {
"metadata": {
"type": "object"
},
"type": {
"type": "string"
},
"value": {
"type": [
"string",
"null"
]
}
},
"type": "object"
},
"hints": "Transform an NGSI building entity representing a hotel into a GraphQL request payload for createHotel. Build a JSON object with query and operationName. Use description.value both as name.value and hasDescription.object.shortDescription.value when available. Parse address.value into hasLocation.object.streetAddress, postalCode, municipality, province, autonomousCommunity and country. If postal code cannot be extracted, keep streetAddress and country without failing.",
"source_fragment": {
"metadata": {},
"type": "string",
"value": null
},
"source_json": {
"address": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"category": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"dataProvider": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"description": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"id": "building:hoteles.ayto-xlsx.141",
"location": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"name": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"status": {
"metadata": {},
"type": "string",
"value": "operational"
},
"subCategory": {
"metadata": {},
"type": "string",
"value": null
},
"type": "building"
},
"task": "synthesize"
},
"response": "{\"jq_expression\":\".subCategory\"}",
"system_prompt": "You generate a jq expression for one target field. Return exactly one flat JSON object and nothing else. Do not wrap the result in markdown. Do not nest the result under keys like result, output, data, or expression. Use exactly this output schema: {\"jq_expression\": string}. \"jq_expression\" must be a JSON string containing only the jq expression for the target field. Use candidate_source_path as the primary source location, verify it against source_json, and use source_fragment as the focused local value. Do not return explanations or extra keys. Example valid output: {\"jq_expression\":\".datetime\"}",
"used_hints": true
},
"stage": "jq_synthesis",
"timestamp": "2026-05-18T15:54:08.843682+00:00"
},
{
"payload": {
"field_expressions": {
"address": ".address",
"category": ".category",
"dataProvider": ".dataProvider",
"description": ".description",
"id": ".id",
"location": ".location",
"name": ".name",
"source": ".source",
"status": ".status",
"subCategory": ".subCategory",
"type": ".type"
},
"jq_filter": "{ \"id\": .id, \"type\": .type, \"address\": .address, \"category\": .category, \"dataProvider\": .dataProvider, \"description\": .description, \"location\": .location, \"name\": .name, \"source\": .source, \"status\": .status, \"subCategory\": .subCategory }",
"validation_passed": true
},
"stage": "generation_complete",
"timestamp": "2026-05-18T15:54:08.856104+00:00"
},
{
"payload": {
"jq_filter": "{ \"id\": .id, \"type\": .type, \"address\": .address, \"category\": .category, \"dataProvider\": .dataProvider, \"description\": .description, \"location\": .location, \"name\": .name, \"source\": .source, \"status\": .status, \"subCategory\": .subCategory }",
"output_json": {
"address": {
"metadata": {},
"type": "string",
"value": "Camino Viejo de Madrid, 38. 28230 Las Rozas."
},
"category": {
"metadata": {},
"type": "string-array",
"value": [
"Hoteles"
]
},
"dataProvider": {
"metadata": {},
"type": "string",
"value": "ayto-xlsx"
},
"description": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"id": "building:hoteles.ayto-xlsx.141",
"location": {
"metadata": {},
"type": "geo:json",
"value": {
"coordinates": [
-3.8565638,
40.4845294
],
"type": "Point"
}
},
"name": {
"metadata": {},
"type": "string",
"value": "Aparthotel TH Las Rozas"
},
"source": {
"metadata": {},
"type": "string",
"value": "https://www.lasrozas.es/ferias-y-fiestas/alojamientos"
},
"status": {
"metadata": {},
"type": "string",
"value": "operational"
},
"subCategory": {
"metadata": {},
"type": "string",
"value": null
},
"type": "building"
},
"schema_valid": true,
"validation_errors": []
},
"stage": "transform_complete",
"timestamp": "2026-05-18T15:54:08.859412+00:00"
}
],
"run_id": "cb7a2a73-8582-4f16-a4b5-4ff97441050b"
}