# Generated by default/object.tt package Paws::Comprehend::EntityRecognizerInputDataConfig; use Moose; has Annotations => (is => 'ro', isa => 'Paws::Comprehend::EntityRecognizerAnnotations'); has AugmentedManifests => (is => 'ro', isa => 'ArrayRef[Paws::Comprehend::AugmentedManifestsListItem]'); has DataFormat => (is => 'ro', isa => 'Str'); has Documents => (is => 'ro', isa => 'Paws::Comprehend::EntityRecognizerDocuments'); has EntityList => (is => 'ro', isa => 'Paws::Comprehend::EntityRecognizerEntityList'); has EntityTypes => (is => 'ro', isa => 'ArrayRef[Paws::Comprehend::EntityTypesListItem]', required => 1); 1; ### main pod documentation begin ### =head1 NAME Paws::Comprehend::EntityRecognizerInputDataConfig =head1 USAGE This class represents one of two things: =head3 Arguments in a call to a service Use the attributes of this class as arguments to methods. You shouldn't make instances of this class. Each attribute should be used as a named argument in the calls that expect this type of object. As an example, if Att1 is expected to be a Paws::Comprehend::EntityRecognizerInputDataConfig object: $service_obj->Method(Att1 => { Annotations => $value, ..., EntityTypes => $value }); =head3 Results returned from an API call Use accessors for each attribute. If Att1 is expected to be an Paws::Comprehend::EntityRecognizerInputDataConfig object: $result = $service_obj->Method(...); $result->Att1->Annotations =head1 DESCRIPTION Specifies the format and location of the input data. =head1 ATTRIBUTES =head2 Annotations => L The S3 location of the CSV file that annotates your training documents. =head2 AugmentedManifests => ArrayRef[L] 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 C to C. =head2 DataFormat => Str The format of your training data: =over =item * C: 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 C or C parameters. You must provide your training documents by using the C parameter. =item * C: 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 C parameter in your request. =back If you don't specify a value, Amazon Comprehend uses C as the default. =head2 Documents => L The S3 location of the folder that contains the training documents for your custom entity recognizer. This parameter is required if you set C to C. =head2 EntityList => L The S3 location of the CSV file that has the entity list for your custom entity recognizer. =head2 B EntityTypes => ArrayRef[L] 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). =head1 SEE ALSO This class forms part of L, describing an object used in L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut