Amazon Comprehend · Schema

ClassifyDocumentResponse

Amazon Web ServicesMachine LearningNatural Language ProcessingText Analysis

Properties

Name Type Description
Classes array The classes used by the document being analyzed. These are used for models trained in multi-class mode. Individual classes are mutually exclusive and each document is expected to have only a single cl
Labels array The labels used in the document being analyzed. These are used for multi-label trained models. Individual labels represent different categories that are related in some manner and are not mutually exc
DocumentMetadata object
DocumentType array The document type for each page in the input document. This field is present in the response only if your request includes the Byte parameter.
Errors array Page-level errors that the system detected while processing the input document. The field is empty if the system encountered no errors.
Warnings array Warnings detected while processing the input document. The response includes a warning if there is a mismatch between the input document type and the model type associated with the endpoint that you s
View JSON Schema on GitHub

JSON Schema

amazon-comprehend-classify-document-response-schema.json Raw ↑
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://artifacts.apis.io/amazon-comprehend/json-schema/amazon-comprehend-classify-document-response-schema.json",
  "title": "ClassifyDocumentResponse",
  "x-generated": "2026-11-11",
  "x-method": "derived",
  "x-generator": "derive-json-schema.py",
  "x-source": "openapi/amazon-comprehend-amazon-comprehend-api-openapi.yml#/components/schemas/ClassifyDocumentResponse",
  "type": "object",
  "properties": {
    "Classes": {
      "type": "array",
      "items": {
        "$ref": "#/$defs/DocumentClass"
      },
      "description": "The classes used by the document being analyzed. These are used for models trained in multi-class mode. Individual classes are mutually exclusive and each document is expected to have only a single class assigned to it. For example, an animal can be a dog or a cat, but not both at the same time. For prompt safety classification, the response includes only two classes (SAFE_PROMPT and UNSAFE_PROMPT), along with a confidence score for each class. The value range of the score is zero to one, where one is the highest confidence."
    },
    "Labels": {
      "type": "array",
      "items": {
        "$ref": "#/$defs/DocumentLabel"
      },
      "description": "The labels used in the document being analyzed. These are used for multi-label trained models. Individual labels represent different categories that are related in some manner and are not mutually exclusive. For example, a movie can be just an action movie, or it can be an action movie, a science fiction movie, and a comedy, all at the same time."
    },
    "DocumentMetadata": {
      "$ref": "#/$defs/DocumentMetadata"
    },
    "DocumentType": {
      "type": "array",
      "items": {
        "$ref": "#/$defs/DocumentTypeListItem"
      },
      "description": "The document type for each page in the input document. This field is present in the response only if your request includes the Byte parameter."
    },
    "Errors": {
      "type": "array",
      "items": {
        "$ref": "#/$defs/ErrorsListItem"
      },
      "description": "Page-level errors that the system detected while processing the input document. The field is empty if the system encountered no errors."
    },
    "Warnings": {
      "type": "array",
      "items": {
        "$ref": "#/$defs/WarningsListItem"
      },
      "description": "Warnings detected while processing the input document. The response includes a warning if there is a mismatch between the input document type and the model type associated with the endpoint that you specified. The response can also include warnings for individual pages that have a mismatch. The field is empty if the system generated no warnings."
    }
  },
  "$defs": {
    "DocumentClass": {
      "type": "object",
      "properties": {
        "Name": {
          "type": "string",
          "description": "The name of the class."
        },
        "Score": {
          "type": "number",
          "description": "The confidence score that Amazon Comprehend has this class correctly attributed."
        },
        "Page": {
          "type": "integer",
          "description": "Page number in the input document. This field is present in the response only if your request includes the Byte parameter."
        }
      }
    },
    "DocumentLabel": {
      "type": "object",
      "properties": {
        "Name": {
          "type": "string",
          "description": "The name of the label."
        },
        "Score": {
          "type": "number",
          "description": "The confidence score that Amazon Comprehend has this label correctly attributed."
        },
        "Page": {
          "type": "integer",
          "description": "Page number where the label occurs. This field is present in the response only if your request includes the Byte parameter."
        }
      }
    },
    "DocumentMetadata": {
      "type": "object",
      "properties": {
        "Pages": {
          "type": "integer",
          "description": "Number of pages in the document."
        },
        "ExtractedCharacters": {
          "type": "array",
          "items": {
            "$ref": "#/$defs/ExtractedCharactersListItem"
          },
          "description": "List of pages in the document, with the number of characters extracted from each page."
        }
      }
    },
    "DocumentTypeListItem": {
      "type": "object",
      "properties": {
        "Page": {
          "type": "integer",
          "description": "Page number."
        },
        "Type": {
          "type": "string",
          "enum": [
            "NATIVE_PDF",
            "SCANNED_PDF",
            "MS_WORD",
            "IMAGE",
            "PLAIN_TEXT",
            "TEXTRACT_DETECT_DOCUMENT_TEXT_JSON",
            "TEXTRACT_ANALYZE_DOCUMENT_JSON"
          ],
          "description": "Document type."
        }
      }
    },
    "ErrorsListItem": {
      "type": "object",
      "properties": {
        "Page": {
          "type": "integer",
          "description": "Page number where the error occurred."
        },
        "ErrorCode": {
          "type": "string",
          "enum": [
            "TEXTRACT_BAD_PAGE",
            "TEXTRACT_PROVISIONED_THROUGHPUT_EXCEEDED",
            "PAGE_CHARACTERS_EXCEEDED",
            "PAGE_SIZE_EXCEEDED",
            "INTERNAL_SERVER_ERROR"
          ],
          "description": "Error code for the cause of the error."
        },
        "ErrorMessage": {
          "type": "string",
          "description": "Text message explaining the reason for the error."
        }
      }
    },
    "ExtractedCharactersListItem": {
      "type": "object",
      "properties": {
        "Page": {
          "type": "integer",
          "description": "Page number."
        },
        "Count": {
          "type": "integer",
          "description": "Number of characters extracted from each page."
        }
      }
    },
    "WarningsListItem": {
      "type": "object",
      "properties": {
        "Page": {
          "type": "integer",
          "description": "Page number in the input document."
        },
        "WarnCode": {
          "type": "string",
          "enum": [
            "INFERENCING_PLAINTEXT_WITH_NATIVE_TRAINED_MODEL",
            "INFERENCING_NATIVE_DOCUMENT_WITH_PLAINTEXT_TRAINED_MODEL"
          ],
          "description": "The type of warning."
        },
        "WarnMessage": {
          "type": "string",
          "description": "Text message associated with the warning."
        }
      }
    }
  }
}

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