[ aws . comprehend ]

classify-document

Description

Creates a new document classification request to analyze a single document in real-time, using a previously created and trained custom model and an endpoint.

See also: AWS API Documentation

See ‘aws help’ for descriptions of global parameters.

Synopsis

  classify-document
--text <value>
--endpoint-arn <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]

Options

--text (string)

The document text to be analyzed.

--endpoint-arn (string)

The Amazon Resource Number (ARN) of the endpoint. For information about endpoints, see Managing endpoints .

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

See ‘aws help’ for descriptions of global parameters.

Output

Classes -> (list)

The classes used by the document being analyzed. These are used for multi-class trained models. 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.

(structure)

Specifies the class that categorizes the document being analyzed

Name -> (string)

The name of the class.

Score -> (float)

The confidence score that Amazon Comprehend has this class correctly attributed.

Labels -> (list)

The labels used 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.

(structure)

Specifies one of the label or labels that categorize the document being analyzed.

Name -> (string)

The name of the label.

Score -> (float)

The confidence score that Amazon Comprehend has this label correctly attributed.