ComprehendMedical / Client / describe_entities_detection_v2_job

describe_entities_detection_v2_job#

ComprehendMedical.Client.describe_entities_detection_v2_job(**kwargs)#

Gets the properties associated with a medical entities detection job. Use this operation to get the status of a detection job.

See also: AWS API Documentation

Request Syntax

response = client.describe_entities_detection_v2_job(
    JobId='string'
)
Parameters:

JobId (string) –

[REQUIRED]

The identifier that Amazon Comprehend Medical generated for the job. The StartEntitiesDetectionV2Job operation returns this identifier in its response.

Return type:

dict

Returns:

Response Syntax

{
    'ComprehendMedicalAsyncJobProperties': {
        'JobId': 'string',
        'JobName': 'string',
        'JobStatus': 'SUBMITTED'|'IN_PROGRESS'|'COMPLETED'|'PARTIAL_SUCCESS'|'FAILED'|'STOP_REQUESTED'|'STOPPED',
        'Message': 'string',
        'SubmitTime': datetime(2015, 1, 1),
        'EndTime': datetime(2015, 1, 1),
        'ExpirationTime': datetime(2015, 1, 1),
        'InputDataConfig': {
            'S3Bucket': 'string',
            'S3Key': 'string'
        },
        'OutputDataConfig': {
            'S3Bucket': 'string',
            'S3Key': 'string'
        },
        'LanguageCode': 'en',
        'DataAccessRoleArn': 'string',
        'ManifestFilePath': 'string',
        'KMSKey': 'string',
        'ModelVersion': 'string'
    }
}

Response Structure

  • (dict) –

    • ComprehendMedicalAsyncJobProperties (dict) –

      An object that contains the properties associated with a detection job.

      • JobId (string) –

        The identifier assigned to the detection job.

      • JobName (string) –

        The name that you assigned to the detection job.

      • JobStatus (string) –

        The current status of the detection job. If the status is FAILED, the Message field shows the reason for the failure.

      • Message (string) –

        A description of the status of a job.

      • SubmitTime (datetime) –

        The time that the detection job was submitted for processing.

      • EndTime (datetime) –

        The time that the detection job completed.

      • ExpirationTime (datetime) –

        The date and time that job metadata is deleted from the server. Output files in your S3 bucket will not be deleted. After the metadata is deleted, the job will no longer appear in the results of the ListEntitiesDetectionV2Job or the ListPHIDetectionJobs operation.

      • InputDataConfig (dict) –

        The input data configuration that you supplied when you created the detection job.

        • S3Bucket (string) –

          The URI of the S3 bucket that contains the input data. The bucket must be in the same region as the API endpoint that you are calling.

        • S3Key (string) –

          The path to the input data files in the S3 bucket.

      • OutputDataConfig (dict) –

        The output data configuration that you supplied when you created the detection job.

        • S3Bucket (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.

        • S3Key (string) –

          The path to the output data files in the S3 bucket. Amazon Comprehend Medical creates an output directory using the job ID so that the output from one job does not overwrite the output of another.

      • LanguageCode (string) –

        The language code of the input documents.

      • DataAccessRoleArn (string) –

        The Amazon Resource Name (ARN) that gives Amazon Comprehend Medical read access to your input data.

      • ManifestFilePath (string) –

        The path to the file that describes the results of a batch job.

      • KMSKey (string) –

        The AWS Key Management Service key, if any, used to encrypt the output files.

      • ModelVersion (string) –

        The version of the model used to analyze the documents. The version number looks like X.X.X. You can use this information to track the model used for a particular batch of documents.

Exceptions