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Class: Aws::Comprehend::Types::EntityRecognizerInputDataConfig

Inherits:
Struct
  • Object
show all
Defined in:
(unknown)

Overview

Note:

When passing EntityRecognizerInputDataConfig as input to an Aws::Client method, you can use a vanilla Hash:

{
  data_format: "COMPREHEND_CSV", # accepts COMPREHEND_CSV, AUGMENTED_MANIFEST
  entity_types: [ # required
    {
      type: "EntityTypeName", # required
    },
  ],
  documents: {
    s3_uri: "S3Uri", # required
  },
  annotations: {
    s3_uri: "S3Uri", # required
  },
  entity_list: {
    s3_uri: "S3Uri", # required
  },
  augmented_manifests: [
    {
      s3_uri: "S3Uri", # required
      attribute_names: ["AttributeNamesListItem"], # required
    },
  ],
}

Specifies the format and location of the input data.

Returned by:

See Also:

Instance Attribute Summary collapse

Instance Attribute Details

#annotations ⇒ Types::EntityRecognizerAnnotations

The S3 location of the CSV file that annotates your training documents.

Returns:

#augmented_manifests ⇒ Array<Types::AugmentedManifestsListItem>

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.

Returns:

#data_format ⇒ String

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.

Possible values:

  • COMPREHEND_CSV
  • AUGMENTED_MANIFEST

Returns:

  • (String) —

    The format of your training data:.

#documents ⇒ Types::EntityRecognizerDocuments

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.

Returns:

#entity_list ⇒ Types::EntityRecognizerEntityList

The S3 location of the CSV file that has the entity list for your custom entity recognizer.

Returns:

#entity_types ⇒ Array<Types::EntityTypesListItem>

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).

Returns:

  • (Array<Types::EntityTypesListItem>) —

    The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer.