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aws_comprehend_entity_recognizer

account_id

Type: STRING

data_access_role_arn

Type: STRING
Provider name: DataAccessRoleArn
Description: The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.

end_time

Type: TIMESTAMP
Provider name: EndTime
Description: The time that the recognizer creation completed.

entity_recognizer_arn

Type: STRING
Provider name: EntityRecognizerArn
Description: The Amazon Resource Name (ARN) that identifies the entity recognizer.

flywheel_arn

Type: STRING
Provider name: FlywheelArn
Description: The Amazon Resource Number (ARN) of the flywheel

input_data_config

Type: STRUCT
Provider name: InputDataConfig
Description: The input data properties of an entity recognizer.

  • annotations
    Type: STRUCT
    Provider name: Annotations
    Description: The S3 location of the CSV file that annotates your training documents.
    • s3_uri
      Type: STRING
      Provider name: S3Uri
      Description: Specifies the Amazon S3 location where the annotations for an entity recognizer are located. The URI must be in the same Region as the API endpoint that you are calling.
    • test_s3_uri
      Type: STRING
      Provider name: TestS3Uri
      Description: Specifies the Amazon S3 location where the test annotations for an entity recognizer are located. The URI must be in the same Region as the API endpoint that you are calling.
  • augmented_manifests
    Type: UNORDERED_LIST_STRUCT
    Provider name: AugmentedManifests
    Description: A list of augmented manifest files that provide training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth. This parameter is required if you set DataFormat to AUGMENTED_MANIFEST.
    • annotation_data_s3_uri
      Type: STRING
      Provider name: AnnotationDataS3Uri
      Description: The S3 prefix to the annotation files that are referred in the augmented manifest file.
    • attribute_names
      Type: UNORDERED_LIST_STRING
      Provider name: AttributeNames
      Description: The JSON attribute that contains the annotations for your training documents. The number of attribute names that you specify depends on whether your augmented manifest file is the output of a single labeling job or a chained labeling job. If your file is the output of a single labeling job, specify the LabelAttributeName key that was used when the job was created in Ground Truth. If your file is the output of a chained labeling job, specify the LabelAttributeName key for one or more jobs in the chain. Each LabelAttributeName key provides the annotations from an individual job.
    • document_type
      Type: STRING
      Provider name: DocumentType
      Description: The type of augmented manifest. PlainTextDocument or SemiStructuredDocument. If you don’t specify, the default is PlainTextDocument.
      • PLAIN_TEXT_DOCUMENT A document type that represents any unicode text that is encoded in UTF-8.
      • SEMI_STRUCTURED_DOCUMENT A document type with positional and structural context, like a PDF. For training with Amazon Comprehend, only PDFs are supported. For inference, Amazon Comprehend support PDFs, DOCX and TXT.
    • s3_uri
      Type: STRING
      Provider name: S3Uri
      Description: The Amazon S3 location of the augmented manifest file.
    • source_documents_s3_uri
      Type: STRING
      Provider name: SourceDocumentsS3Uri
      Description: The S3 prefix to the source files (PDFs) that are referred to in the augmented manifest file.
    • split
      Type: STRING
      Provider name: Split
      Description: The purpose of the data you’ve provided in the augmented manifest. You can either train or test this data. If you don’t specify, the default is train. TRAIN - all of the documents in the manifest will be used for training. If no test documents are provided, Amazon Comprehend will automatically reserve a portion of the training documents for testing. TEST - all of the documents in the manifest will be used for testing.
  • data_format
    Type: STRING
    Provider name: DataFormat
    Description: The format of your training data:
    • COMPREHEND_CSV: A CSV file that supplements your training documents. The CSV file contains information about the custom entities that your trained model will detect. The required format of the file depends on whether you are providing annotations or an entity list. If you use this value, you must provide your CSV file by using either the Annotations or EntityList parameters. You must provide your training documents by using the Documents parameter.
    • AUGMENTED_MANIFEST: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its labels. Each label annotates a named entity in the training document. If you use this value, you must provide the AugmentedManifests parameter in your request.
    If you don’t specify a value, Amazon Comprehend uses COMPREHEND_CSV as the default.
  • documents
    Type: STRUCT
    Provider name: Documents
    Description: The S3 location of the folder that contains the training documents for your custom entity recognizer. This parameter is required if you set DataFormat to COMPREHEND_CSV.
    • input_format
      Type: STRING
      Provider name: InputFormat
      Description: Specifies how the text in an input file should be processed. This is optional, and the default is ONE_DOC_PER_LINE. 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.
    • s3_uri
      Type: STRING
      Provider name: S3Uri
      Description: Specifies the Amazon S3 location where the training documents for an entity recognizer are located. The URI must be in the same Region as the API endpoint that you are calling.
    • test_s3_uri
      Type: STRING
      Provider name: TestS3Uri
      Description: Specifies the Amazon S3 location where the test documents for an entity recognizer are located. The URI must be in the same Amazon Web Services Region as the API endpoint that you are calling.
  • entity_list
    Type: STRUCT
    Provider name: EntityList
    Description: The S3 location of the CSV file that has the entity list for your custom entity recognizer.
    • s3_uri
      Type: STRING
      Provider name: S3Uri
      Description: Specifies the Amazon S3 location where the entity list is located. The URI must be in the same Region as the API endpoint that you are calling.
  • entity_types
    Type: UNORDERED_LIST_STRUCT
    Provider name: EntityTypes
    Description: The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer. Any entity types that you don’t specify are ignored. A maximum of 25 entity types can be used at one time to train an entity recognizer. Entity types must not contain the following invalid characters: \n (line break), \n (escaped line break), \r (carriage return), \r (escaped carriage return), \t (tab), \t (escaped tab), space, and , (comma).
    • type
      Type: STRING
      Provider name: Type
      Description: An entity type within a labeled training dataset that Amazon Comprehend uses to train a custom entity recognizer. Entity types must not contain the following invalid characters: \n (line break), \n (escaped line break, \r (carriage return), \r (escaped carriage return), \t (tab), \t (escaped tab), and , (comma).

language_code

Type: STRING
Provider name: LanguageCode
Description: The language of the input documents. All documents must be in the same language. Only English (“en”) is currently supported.

message

Type: STRING
Provider name: Message
Description: A description of the status of the recognizer.

model_kms_key_id

Type: STRING
Provider name: ModelKmsKeyId
Description: ID for the KMS key that Amazon Comprehend uses to encrypt trained custom models. The ModelKmsKeyId 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”

output_data_config

Type: STRUCT
Provider name: OutputDataConfig
Description: Output data configuration.

  • flywheel_stats_s3_prefix
    Type: STRING
    Provider name: FlywheelStatsS3Prefix
    Description: The Amazon S3 prefix for the data lake location of the flywheel statistics.

recognizer_metadata

Type: STRUCT
Provider name: RecognizerMetadata
Description: Provides information about an entity recognizer.

  • entity_types
    Type: UNORDERED_LIST_STRUCT
    Provider name: EntityTypes
    Description: Entity types from the metadata of an entity recognizer.
    • evaluation_metrics
      Type: STRUCT
      Provider name: EvaluationMetrics
      Description: Detailed information about the accuracy of the entity recognizer for a specific item on the list of entity types.
      • f1_score
        Type: DOUBLE
        Provider name: F1Score
        Description: A measure of how accurate the recognizer results are for a specific entity type in the test data. It is derived from the Precision and Recall values. The F1Score is the harmonic average of the two scores. The highest score is 1, and the worst score is 0.
      • precision
        Type: DOUBLE
        Provider name: Precision
        Description: A measure of the usefulness of the recognizer results for a specific entity type in the test data. High precision means that the recognizer returned substantially more relevant results than irrelevant ones.
      • recall
        Type: DOUBLE
        Provider name: Recall
        Description: A measure of how complete the recognizer results are for a specific entity type in the test data. High recall means that the recognizer returned most of the relevant results.
    • number_of_train_mentions
      Type: INT32
      Provider name: NumberOfTrainMentions
      Description: Indicates the number of times the given entity type was seen in the training data.
    • type
      Type: STRING
      Provider name: Type
      Description: Type of entity from the list of entity types in the metadata of an entity recognizer.
  • evaluation_metrics
    Type: STRUCT
    Provider name: EvaluationMetrics
    Description: Detailed information about the accuracy of an entity recognizer.
    • f1_score
      Type: DOUBLE
      Provider name: F1Score
      Description: A measure of how accurate the recognizer results are for the test data. It is derived from the Precision and Recall values. The F1Score is the harmonic average of the two scores. For plain text entity recognizer models, the range is 0 to 100, where 100 is the best score. For PDF/Word entity recognizer models, the range is 0 to 1, where 1 is the best score.
    • precision
      Type: DOUBLE
      Provider name: Precision
      Description: A measure of the usefulness of the recognizer results in the test data. High precision means that the recognizer returned substantially more relevant results than irrelevant ones.
    • recall
      Type: DOUBLE
      Provider name: Recall
      Description: A measure of how complete the recognizer results are for the test data. High recall means that the recognizer returned most of the relevant results.
  • number_of_test_documents
    Type: INT32
    Provider name: NumberOfTestDocuments
    Description: The number of documents in the input data that were used to test the entity recognizer. Typically this is 10 to 20 percent of the input documents.
  • number_of_trained_documents
    Type: INT32
    Provider name: NumberOfTrainedDocuments
    Description: The number of documents in the input data that were used to train the entity recognizer. Typically this is 80 to 90 percent of the input documents.

source_model_arn

Type: STRING
Provider name: SourceModelArn
Description: The Amazon Resource Name (ARN) of the source model. This model was imported from a different Amazon Web Services account to create the entity recognizer model in your Amazon Web Services account.

status

Type: STRING
Provider name: Status
Description: Provides the status of the entity recognizer.

submit_time

Type: TIMESTAMP
Provider name: SubmitTime
Description: The time that the recognizer was submitted for processing.

tags

Type: UNORDERED_LIST_STRING

training_end_time

Type: TIMESTAMP
Provider name: TrainingEndTime
Description: The time that training of the entity recognizer was completed.

training_start_time

Type: TIMESTAMP
Provider name: TrainingStartTime
Description: The time that training of the entity recognizer started.

version_name

Type: STRING
Provider name: VersionName
Description: The version name you assigned to the entity recognizer.

volume_kms_key_id

Type: STRING
Provider name: VolumeKmsKeyId
Description: 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

Type: STRUCT
Provider name: VpcConfig
Description: Configuration parameters for a private Virtual Private Cloud (VPC) containing the resources you are using for your custom entity recognizer. For more information, see Amazon VPC.

  • security_group_ids
    Type: UNORDERED_LIST_STRING
    Provider name: SecurityGroupIds
    Description: 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.
  • subnets
    Type: UNORDERED_LIST_STRING
    Provider name: Subnets
    Description: 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.