AWS CLI Command Reference

[ aws . comprehend ]

start-document-classification-job

Description

Starts an asynchronous document classification job using a custom classification model. Use the DescribeDocumentClassificationJob operation to track the progress of the job.

See also: AWS API Documentation

Synopsis

  start-document-classification-job
[--job-name <value>]
[--document-classifier-arn <value>]
--input-data-config <value>
--output-data-config <value>
--data-access-role-arn <value>
[--client-request-token <value>]
[--volume-kms-key-id <value>]
[--vpc-config <value>]
[--tags <value>]
[--flywheel-arn <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]
[--cli-binary-format <value>]
[--no-cli-pager]
[--cli-auto-prompt]
[--no-cli-auto-prompt]

Options

--job-name (string)

The identifier of the job.

--document-classifier-arn (string)

The Amazon Resource Name (ARN) of the document classifier to use to process the job.

--input-data-config (structure)

Specifies the format and location of the input data for the job.

S3Uri -> (string)

The Amazon S3 URI for the input data. The URI must be in same Region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of data files.

For example, if you use the URI S3://bucketName/prefix , if the prefix is a single file, Amazon Comprehend uses that file as input. If more than one file begins with the prefix, Amazon Comprehend uses all of them as input.

InputFormat -> (string)

Specifies how the text in an input file should be processed:

  • ONE_DOC_PER_FILE - Each file is considered a separate document. Use this option when you are processing large documents, such as newspaper articles or scientific papers.
  • ONE_DOC_PER_LINE - Each line in a file is considered a separate document. Use this option when you are processing many short documents, such as text messages.

DocumentReaderConfig -> (structure)

Provides configuration parameters to override the default actions for extracting text from PDF documents and image files.

DocumentReadAction -> (string)

This field defines the Amazon Textract API operation that Amazon Comprehend uses to extract text from PDF files and image files. Enter one of the following values:

  • TEXTRACT_DETECT_DOCUMENT_TEXT - The Amazon Comprehend service uses the DetectDocumentText API operation.
  • TEXTRACT_ANALYZE_DOCUMENT - The Amazon Comprehend service uses the AnalyzeDocument API operation.

DocumentReadMode -> (string)

Determines the text extraction actions for PDF files. Enter one of the following values:

  • SERVICE_DEFAULT - use the Amazon Comprehend service defaults for PDF files.
  • FORCE_DOCUMENT_READ_ACTION - Amazon Comprehend uses the Textract API specified by DocumentReadAction for all PDF files, including digital PDF files.

FeatureTypes -> (list)

Specifies the type of Amazon Textract features to apply. If you chose TEXTRACT_ANALYZE_DOCUMENT as the read action, you must specify one or both of the following values:

  • TABLES - Returns additional information about any tables that are detected in the input document.
  • FORMS - Returns additional information about any forms that are detected in the input document.

(string)

TABLES or FORMS

Shorthand Syntax:

S3Uri=string,InputFormat=string,DocumentReaderConfig={DocumentReadAction=string,DocumentReadMode=string,FeatureTypes=[string,string]}

JSON Syntax:

{
  "S3Uri": "string",
  "InputFormat": "ONE_DOC_PER_FILE"|"ONE_DOC_PER_LINE",
  "DocumentReaderConfig": {
    "DocumentReadAction": "TEXTRACT_DETECT_DOCUMENT_TEXT"|"TEXTRACT_ANALYZE_DOCUMENT",
    "DocumentReadMode": "SERVICE_DEFAULT"|"FORCE_DOCUMENT_READ_ACTION",
    "FeatureTypes": ["TABLES"|"FORMS", ...]
  }
}

--output-data-config (structure)

Specifies where to send the output files.

S3Uri -> (string)

When you use the OutputDataConfig object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same Region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output file.

When the topic detection job is finished, the service creates an output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz . It is a compressed archive that contains the ouput of the operation.

For a PII entity detection job, the output file is plain text, not a compressed archive. The output file name is the same as the input file, with .out appended at the end.

KmsKeyId -> (string)

ID for the Amazon Web Services Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. Specify the Key Id of a symmetric key, because you cannot use an asymmetric key for uploading data to S3.

The KmsKeyId can be one of the following formats:

  • KMS Key ID: "1234abcd-12ab-34cd-56ef-1234567890ab"
  • Amazon Resource Name (ARN) of a KMS Key: "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
  • KMS Key Alias: "alias/ExampleAlias"
  • ARN of a KMS Key Alias: "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"

Shorthand Syntax:

S3Uri=string,KmsKeyId=string

JSON Syntax:

{
  "S3Uri": "string",
  "KmsKeyId": "string"
}

--data-access-role-arn (string)

The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.

--client-request-token (string)

A unique identifier for the request. If you do not set the client request token, Amazon Comprehend generates one.

--volume-kms-key-id (string)

ID for the Amazon Web Services Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:

  • KMS Key ID: "1234abcd-12ab-34cd-56ef-1234567890ab"
  • Amazon Resource Name (ARN) of a KMS Key: "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"

--vpc-config (structure)

Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your document classification job. For more information, see Amazon VPC .

SecurityGroupIds -> (list)

The ID number for a security group on an instance of your private VPC. Security groups on your VPC function serve as a virtual firewall to control inbound and outbound traffic and provides security for the resources that you’ll be accessing on the VPC. This ID number is preceded by “sg-”, for instance: “sg-03b388029b0a285ea”. For more information, see Security Groups for your VPC .

(string)

Subnets -> (list)

The ID for each subnet being used in your private VPC. This subnet is a subset of the a range of IPv4 addresses used by the VPC and is specific to a given availability zone in the VPC’s Region. This ID number is preceded by “subnet-”, for instance: “subnet-04ccf456919e69055”. For more information, see VPCs and Subnets .

(string)

Shorthand Syntax:

SecurityGroupIds=string,string,Subnets=string,string

JSON Syntax:

{
  "SecurityGroupIds": ["string", ...],
  "Subnets": ["string", ...]
}

--tags (list)

Tags to associate with the document classification job. A tag is a key-value pair that adds metadata to a resource used by Amazon Comprehend. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department.

(structure)

A key-value pair that adds as a metadata to a resource used by Amazon Comprehend. For example, a tag with the key-value pair ‘Department’:’Sales’ might be added to a resource to indicate its use by a particular department.

Key -> (string)

The initial part of a key-value pair that forms a tag associated with a given resource. For instance, if you want to show which resources are used by which departments, you might use “Department” as the key portion of the pair, with multiple possible values such as “sales,” “legal,” and “administration.”

Value -> (string)

The second part of a key-value pair that forms a tag associated with a given resource. For instance, if you want to show which resources are used by which departments, you might use “Department” as the initial (key) portion of the pair, with a value of “sales” to indicate the sales department.

Shorthand Syntax:

Key=string,Value=string ...

JSON Syntax:

[
  {
    "Key": "string",
    "Value": "string"
  }
  ...
]

--flywheel-arn (string)

The Amazon Resource Number (ARN) of the flywheel associated with the model to use.

--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.

Global Options

--debug (boolean)

Turn on debug logging.

--endpoint-url (string)

Override command’s default URL with the given URL.

--no-verify-ssl (boolean)

By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.

--no-paginate (boolean)

Disable automatic pagination. If automatic pagination is disabled, the AWS CLI will only make one call, for the first page of results.

--output (string)

The formatting style for command output.

  • json
  • text
  • table
  • yaml
  • yaml-stream

--query (string)

A JMESPath query to use in filtering the response data.

--profile (string)

Use a specific profile from your credential file.

--region (string)

The region to use. Overrides config/env settings.

--version (string)

Display the version of this tool.

--color (string)

Turn on/off color output.

  • on
  • off
  • auto

--no-sign-request (boolean)

Do not sign requests. Credentials will not be loaded if this argument is provided.

--ca-bundle (string)

The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.

--cli-read-timeout (int)

The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.

--cli-connect-timeout (int)

The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.

--cli-binary-format (string)

The formatting style to be used for binary blobs. The default format is base64. The base64 format expects binary blobs to be provided as a base64 encoded string. The raw-in-base64-out format preserves compatibility with AWS CLI V1 behavior and binary values must be passed literally. When providing contents from a file that map to a binary blob fileb:// will always be treated as binary and use the file contents directly regardless of the cli-binary-format setting. When using file:// the file contents will need to properly formatted for the configured cli-binary-format.

  • base64
  • raw-in-base64-out

--no-cli-pager (boolean)

Disable cli pager for output.

--cli-auto-prompt (boolean)

Automatically prompt for CLI input parameters.

--no-cli-auto-prompt (boolean)

Disable automatically prompt for CLI input parameters.

Examples

Note

To use the following examples, you must have the AWS CLI installed and configured. See the Getting started guide in the AWS CLI User Guide for more information.

Unless otherwise stated, all examples have unix-like quotation rules. These examples will need to be adapted to your terminal’s quoting rules. See Using quotation marks with strings in the AWS CLI User Guide .

To start document classification job

The following start-document-classification-job example starts a document classification job with a custom model on all of the files at the address specified by the --input-data-config tag. In this example, the input S3 bucket contains SampleSMStext1.txt, SampleSMStext2.txt, and SampleSMStext3.txt. The model was previously trained on document classifications of spam and non-spam, or, “ham”, SMS messages. When the job is complete, output.tar.gz is put at the location specified by the --output-data-config tag. output.tar.gz contains predictions.jsonl which lists the classification of each document. The Json output is printed on one line per file, but is formatted here for readability.

aws comprehend start-document-classification-job \
    --job-name exampleclassificationjob \
    --input-data-config "S3Uri=s3://DOC-EXAMPLE-BUCKET-INPUT/jobdata/" \
    --output-data-config "S3Uri=s3://DOC-EXAMPLE-DESTINATION-BUCKET/testfolder/" \
    --data-access-role-arn arn:aws:iam::111122223333:role/service-role/AmazonComprehendServiceRole-example-role \
    --document-classifier-arn arn:aws:comprehend:us-west-2:111122223333:document-classifier/mymodel/version/12

Contents of SampleSMStext1.txt:

"CONGRATULATIONS! TXT 2155550100 to win $5000"

Contents of SampleSMStext2.txt:

"Hi, when do you want me to pick you up from practice?"

Contents of SampleSMStext3.txt:

"Plz send bank account # to 2155550100 to claim prize!!"

Output:

{
    "JobId": "e758dd56b824aa717ceab551fEXAMPLE",
    "JobArn": "arn:aws:comprehend:us-west-2:111122223333:document-classification-job/e758dd56b824aa717ceab551fEXAMPLE",
    "JobStatus": "SUBMITTED"
}

Contents of predictions.jsonl:

{"File": "SampleSMSText1.txt", "Line": "0", "Classes": [{"Name": "spam", "Score": 0.9999}, {"Name": "ham", "Score": 0.0001}]}
{"File": "SampleSMStext2.txt", "Line": "0", "Classes": [{"Name": "ham", "Score": 0.9994}, {"Name": "spam", "Score": 0.0006}]}
{"File": "SampleSMSText3.txt", "Line": "0", "Classes": [{"Name": "spam", "Score": 0.9999}, {"Name": "ham", "Score": 0.0001}]}

For more information, see Custom Classification in the Amazon Comprehend Developer Guide.

Output

JobId -> (string)

The identifier generated for the job. To get the status of the job, use this identifier with the DescribeDocumentClassificationJob operation.

JobArn -> (string)

The Amazon Resource Name (ARN) of the document classification job. It is a unique, fully qualified identifier for the job. It includes the Amazon Web Services account, Amazon Web Services Region, and the job ID. The format of the ARN is as follows:

arn:<partition>:comprehend:<region>:<account-id>:document-classification-job/<job-id>

The following is an example job ARN:

arn:aws:comprehend:us-west-2:111122223333:document-classification-job/1234abcd12ab34cd56ef1234567890ab

JobStatus -> (string)

The status of the job:

  • SUBMITTED - The job has been received and queued for processing.
  • IN_PROGRESS - Amazon Comprehend is processing the job.
  • COMPLETED - The job was successfully completed and the output is available.
  • FAILED - The job did not complete. For details, use the DescribeDocumentClassificationJob operation.
  • STOP_REQUESTED - Amazon Comprehend has received a stop request for the job and is processing the request.
  • STOPPED - The job was successfully stopped without completing.

DocumentClassifierArn -> (string)

The ARN of the custom classification model.
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