Returns a value from an extra_data object you supply in an asynchronous extraction request. Use this method to bring request-time context into a config's output so validations, postprocessors, and computed field methods can read it.

For information about attaching extra_data to a request, see the asynchronous extraction endpoints, for example, the Generate upload URL endpoint.

Common use cases include:

Chain extractions for cross-document validation: Extract fields from a first document (for example, name and date of birth from a loan application), then pass them as extra_data into a subsequent extraction request for the loan applicant's bank statement. The config for the bank statement compares the extra_data values to the values in the bank statement and outputs Boolean values to indicate if the applicant's name and date of birth are consistent in both documents.
Incorporating external data: After extracting a VIN from an auto insurance document, call a third-party lookup service and pass the result (for example, recorded mileage) back as extra_data in a follow-up request. The config uses the Extra Data method with the Custom Computation method to flag any discrepancy between the lookup value and what the document shows.

flowchart LR
    A["External context\n(system of record,\nprior extraction,\nagent reasoning)"] -->|"extra_data"| C["Sensible\nasync extraction"]
    B["Document"] --> C
    C --> D["Output\n(extracted fields +\nvalidated / transformed\nfields + extra_data echoed)"]

Parameters

The following parameters are in the computed field's global Method parameter:

key	value	description
id (required)	`extraData`
key (required)	string	Key to look up in the request's `extra_data` object. If the request omits `extra_data`, if the object doesn't contain the specified key, or if the specified key's value is null, Sensible returns null. These cases aren't distinguishable in the output. The `extra_data` object must be flat: strings, numbers, booleans, or null. Nested objects and arrays aren't supported. When you submit a portfolio extraction with `extra_data`, Sensible passes the same object to every document extracted from the portfolio. For example, if a portfolio contains an auto insurance declarations page and a loan application, both configs can independently look up the same `extra_data` keys and produce their own computed fields based on them.

Examples

The following example uses extra_data to cross-check values from a policy management system against a GEICO auto insurance declarations page. Numeric values (deductibles) use the Custom Computation method for exact equality comparison. A vehicle description uses the LLM-based Query Group method with the Source IDs parameter for a semantic comparison that handles format differences between systems. For example, "NISSAN ROGUE 2010" (policy system) matches "2010 Nissan Rogue" (document) even though the strings aren't equal.

Config

{
  "fields": [
    {
      "id": "collision_deductible",
      "type": "currency",
      "anchor": {
        "match": [
          { "text": "Coverages", "type": "startsWith" },
          { "text": "Collision", "type": "startsWith" }
        ]
      },
      "method": {
        "id": "row",
        "position": "right",
        "tiebreaker": "first" /* leftmost value = the Limits and/or Deductibles column */
      }
    },
    {
      "id": "comprehensive_deductible",
      "type": "currency",
      "anchor": {
        "match": [
          { "text": "Coverages", "type": "startsWith" },
          { "text": "Comprehensive", "type": "startsWith" }
        ]
      },
      "method": {
        "id": "row",
        "position": "right",
        "tiebreaker": "first" /* leftmost value = the Limits and/or Deductibles column */
      }
    },
    {
      "id": "expected_insured_vehicle" /* in fields (not computed_fields) so source_ids can reference it below */,
      "method": { "id": "extraData", "key": "expected_insured_vehicle" }
    },
    {
      "method": {
        "id": "queryGroup",
        "queries": [
          {
            "id": "insured_vehicle",
            "description": "year, make, and model of the first vehicle listed on the policy",
            "type": "string"
          }
        ]
      }
    },
    {
      "method": {
        "id": "queryGroup",
        "source_ids": [
          "expected_insured_vehicle",
          "insured_vehicle"
        ] /* gives the LLM both values as context for a semantic comparison */,
        "queries": [
          {
            "id": "vehicle_matches",
             /* expected output is true; vehicle names vary but are semantically the same*/
            "description": "Do these two vehicle descriptions refer to the same vehicle? Ignore differences in capitalization and word order. Answer true or false.",
            "type": "boolean"
          }
        ]
      }
    },
    {
      "id": "expected_collision_deductible" /* pulled from the request's extra_data object, expected value is 500, which matches the actual document data */,
      "method": { "id": "extraData", "key": "expected_collision_deductible" }
    },
    {
      "id": "expected_comprehensive_deductible" /* pulled from the request's extra_data object, expected value is 300, which doesn't match the actual document data */,
      "method": {
        "id": "extraData",
        "key": "expected_comprehensive_deductible"
      }
    },
    {
      "id": "collision_deductible_matches" /* expected output is true; document's deductible matches what the upstream system expects */,
      "method": {
        "id": "customComputation",
        "jsonLogic": {
          "==": [
            { "var": "collision_deductible.value" },
            { "var": "expected_collision_deductible.value" }
          ]
        }
      }
    },
    {
      "id": "comprehensive_deductible_matches" /* expected output is false; document's deductible doesn't match what the upstream system expects */,
      "method": {
        "id": "customComputation",
        "jsonLogic": {
          "==": [
            { "var": "comprehensive_deductible.value" },
            { "var": "expected_comprehensive_deductible.value" }
          ]
        }
      }
    }
  ]
}

Request

To provide the extra data for the preceding config:

create a document type in the Sensible app using the following example document
add a config to the document type using the preceding SenseML and publish the config to production
run the following command in a terminal, substituting your document type and your API key:

curl --location 'https://api.sensible.so/v0/extract_from_url/your_doc_type' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--data '{
  "document_url": "https://raw.githubusercontent.com/sensible-hq/sensible-docs/v0/assets/pdfs/extra_data.pdf",
  "extra_data": {
    "expected_collision_deductible": 500,
    "expected_comprehensive_deductible": 300,
    "expected_insured_vehicle": "NISSAN ROGUE 2010"
  }
}'

Example document

The following image shows the example document used with this example config:

Example document	Download link

Output

{
        "collision_deductible": {
            "source": "$500",
            "value": 500,
            "unit": "$",
            "type": "currency"
        },
        "comprehensive_deductible": {
            "source": "$250",
            "value": 250,
            "unit": "$",
            "type": "currency"
        },
        "expected_insured_vehicle": {
            "value": "NISSAN ROGUE 2010",
            "type": "string"
        },
        "insured_vehicle": {
            "value": "2010 Nissan Rogue",
            "type": "string",
            "confidenceSignal": "confident_answer"
        },
        "vehicle_matches": {
            "value": true,
            "type": "boolean",
            "confidenceSignal": "not_supported"
        },
        "expected_collision_deductible": {
            "value": 500,
            "type": "number"
        },
        "expected_comprehensive_deductible": {
            "value": 300,
            "type": "number"
        },
        "collision_deductible_matches": {
            "value": true,
            "type": "boolean"
        },
        "comprehensive_deductible_matches": {
            "value": false,
            "type": "boolean"
        }
    }

In the preceding output, the vehicle_matches field is true even though "NISSAN ROGUE 2010" (policy system) doesn't equal "2010 Nissan Rogue" (document). The LLM recognizes they refer to the same vehicle. The collision_deductible_matches field is true because the deductible ($500) matches the expected value. The comprehensive_deductible_matches field is false because the document shows $250, not the expected $300.