PNG  IHDR;IDATxܻn0K )(pA 7LeG{ §㻢|ذaÆ 6lذaÆ 6lذaÆ 6lom$^yذag5bÆ 6lذaÆ 6lذa{ 6lذaÆ `}HFkm,mӪôô! x|'ܢ˟;E:9&ᶒ}{v]n&6 h_tڠ͵-ҫZ;Z$.Pkž)!o>}leQfJTu іچ\X=8Rن4`Vwl>nG^is"ms$ui?wbs[m6K4O.4%/bC%t Mז -lG6mrz2s%9s@-k9=)kB5\+͂Zsٲ Rn~GRC wIcIn7jJhۛNCS|j08yiHKֶۛkɈ+;SzL/F*\Ԕ#"5m2[S=gnaPeғL lذaÆ 6l^ḵaÆ 6lذaÆ 6lذa; _ذaÆ 6lذaÆ 6lذaÆ RIENDB` package Paws::Comprehend; use Moose; sub service { 'comprehend' } sub signing_name { 'comprehend' } sub version { '2017-11-27' } sub target_prefix { 'Comprehend_20171127' } sub json_version { "1.1" } has max_attempts => (is => 'ro', isa => 'Int', default => 5); has retry => (is => 'ro', isa => 'HashRef', default => sub { { base => 'rand', type => 'exponential', growth_factor => 2 } }); has retriables => (is => 'ro', isa => 'ArrayRef', default => sub { [ ] }); with 'Paws::API::Caller', 'Paws::API::EndpointResolver', 'Paws::Net::V4Signature', 'Paws::Net::JsonCaller'; sub BatchDetectDominantLanguage { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::BatchDetectDominantLanguage', @_); return $self->caller->do_call($self, $call_object); } sub BatchDetectEntities { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::BatchDetectEntities', @_); return $self->caller->do_call($self, $call_object); } sub BatchDetectKeyPhrases { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::BatchDetectKeyPhrases', @_); return $self->caller->do_call($self, $call_object); } sub BatchDetectSentiment { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::BatchDetectSentiment', @_); return $self->caller->do_call($self, $call_object); } sub BatchDetectSyntax { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::BatchDetectSyntax', @_); return $self->caller->do_call($self, $call_object); } sub ClassifyDocument { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ClassifyDocument', @_); return $self->caller->do_call($self, $call_object); } sub ContainsPiiEntities { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ContainsPiiEntities', @_); return $self->caller->do_call($self, $call_object); } sub CreateDocumentClassifier { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::CreateDocumentClassifier', @_); return $self->caller->do_call($self, $call_object); } sub CreateEndpoint { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::CreateEndpoint', @_); return $self->caller->do_call($self, $call_object); } sub CreateEntityRecognizer { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::CreateEntityRecognizer', @_); return $self->caller->do_call($self, $call_object); } sub DeleteDocumentClassifier { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DeleteDocumentClassifier', @_); return $self->caller->do_call($self, $call_object); } sub DeleteEndpoint { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DeleteEndpoint', @_); return $self->caller->do_call($self, $call_object); } sub DeleteEntityRecognizer { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DeleteEntityRecognizer', @_); return $self->caller->do_call($self, $call_object); } sub DescribeDocumentClassificationJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DescribeDocumentClassificationJob', @_); return $self->caller->do_call($self, $call_object); } sub DescribeDocumentClassifier { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DescribeDocumentClassifier', @_); return $self->caller->do_call($self, $call_object); } sub DescribeDominantLanguageDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DescribeDominantLanguageDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub DescribeEndpoint { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DescribeEndpoint', @_); return $self->caller->do_call($self, $call_object); } sub DescribeEntitiesDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DescribeEntitiesDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub DescribeEntityRecognizer { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DescribeEntityRecognizer', @_); return $self->caller->do_call($self, $call_object); } sub DescribeEventsDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DescribeEventsDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub DescribeKeyPhrasesDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DescribeKeyPhrasesDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub DescribePiiEntitiesDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DescribePiiEntitiesDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub DescribeSentimentDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DescribeSentimentDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub DescribeTopicsDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DescribeTopicsDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub DetectDominantLanguage { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DetectDominantLanguage', @_); return $self->caller->do_call($self, $call_object); } sub DetectEntities { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DetectEntities', @_); return $self->caller->do_call($self, $call_object); } sub DetectKeyPhrases { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DetectKeyPhrases', @_); return $self->caller->do_call($self, $call_object); } sub DetectPiiEntities { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DetectPiiEntities', @_); return $self->caller->do_call($self, $call_object); } sub DetectSentiment { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DetectSentiment', @_); return $self->caller->do_call($self, $call_object); } sub DetectSyntax { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::DetectSyntax', @_); return $self->caller->do_call($self, $call_object); } sub ListDocumentClassificationJobs { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ListDocumentClassificationJobs', @_); return $self->caller->do_call($self, $call_object); } sub ListDocumentClassifiers { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ListDocumentClassifiers', @_); return $self->caller->do_call($self, $call_object); } sub ListDominantLanguageDetectionJobs { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ListDominantLanguageDetectionJobs', @_); return $self->caller->do_call($self, $call_object); } sub ListEndpoints { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ListEndpoints', @_); return $self->caller->do_call($self, $call_object); } sub ListEntitiesDetectionJobs { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ListEntitiesDetectionJobs', @_); return $self->caller->do_call($self, $call_object); } sub ListEntityRecognizers { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ListEntityRecognizers', @_); return $self->caller->do_call($self, $call_object); } sub ListEventsDetectionJobs { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ListEventsDetectionJobs', @_); return $self->caller->do_call($self, $call_object); } sub ListKeyPhrasesDetectionJobs { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ListKeyPhrasesDetectionJobs', @_); return $self->caller->do_call($self, $call_object); } sub ListPiiEntitiesDetectionJobs { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ListPiiEntitiesDetectionJobs', @_); return $self->caller->do_call($self, $call_object); } sub ListSentimentDetectionJobs { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ListSentimentDetectionJobs', @_); return $self->caller->do_call($self, $call_object); } sub ListTagsForResource { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ListTagsForResource', @_); return $self->caller->do_call($self, $call_object); } sub ListTopicsDetectionJobs { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::ListTopicsDetectionJobs', @_); return $self->caller->do_call($self, $call_object); } sub StartDocumentClassificationJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StartDocumentClassificationJob', @_); return $self->caller->do_call($self, $call_object); } sub StartDominantLanguageDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StartDominantLanguageDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub StartEntitiesDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StartEntitiesDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub StartEventsDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StartEventsDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub StartKeyPhrasesDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StartKeyPhrasesDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub StartPiiEntitiesDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StartPiiEntitiesDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub StartSentimentDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StartSentimentDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub StartTopicsDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StartTopicsDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub StopDominantLanguageDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StopDominantLanguageDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub StopEntitiesDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StopEntitiesDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub StopEventsDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StopEventsDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub StopKeyPhrasesDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StopKeyPhrasesDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub StopPiiEntitiesDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StopPiiEntitiesDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub StopSentimentDetectionJob { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StopSentimentDetectionJob', @_); return $self->caller->do_call($self, $call_object); } sub StopTrainingDocumentClassifier { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StopTrainingDocumentClassifier', @_); return $self->caller->do_call($self, $call_object); } sub StopTrainingEntityRecognizer { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::StopTrainingEntityRecognizer', @_); return $self->caller->do_call($self, $call_object); } sub TagResource { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::TagResource', @_); return $self->caller->do_call($self, $call_object); } sub UntagResource { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::UntagResource', @_); return $self->caller->do_call($self, $call_object); } sub UpdateEndpoint { my $self = shift; my $call_object = $self->new_with_coercions('Paws::Comprehend::UpdateEndpoint', @_); return $self->caller->do_call($self, $call_object); } sub ListAllDocumentClassificationJobs { my $self = shift; my $callback = shift @_ if (ref($_[0]) eq 'CODE'); my $result = $self->ListDocumentClassificationJobs(@_); my $next_result = $result; if (not defined $callback) { while ($next_result->NextToken) { $next_result = $self->ListDocumentClassificationJobs(@_, NextToken => $next_result->NextToken); push @{ $result->DocumentClassificationJobPropertiesList }, @{ $next_result->DocumentClassificationJobPropertiesList }; } return $result; } else { while ($result->NextToken) { $callback->($_ => 'DocumentClassificationJobPropertiesList') foreach (@{ $result->DocumentClassificationJobPropertiesList }); $result = $self->ListDocumentClassificationJobs(@_, NextToken => $result->NextToken); } $callback->($_ => 'DocumentClassificationJobPropertiesList') foreach (@{ $result->DocumentClassificationJobPropertiesList }); } return undef } sub ListAllDocumentClassifiers { my $self = shift; my $callback = shift @_ if (ref($_[0]) eq 'CODE'); my $result = $self->ListDocumentClassifiers(@_); my $next_result = $result; if (not defined $callback) { while ($next_result->NextToken) { $next_result = $self->ListDocumentClassifiers(@_, NextToken => $next_result->NextToken); push @{ $result->DocumentClassifierPropertiesList }, @{ $next_result->DocumentClassifierPropertiesList }; } return $result; } else { while ($result->NextToken) { $callback->($_ => 'DocumentClassifierPropertiesList') foreach (@{ $result->DocumentClassifierPropertiesList }); $result = $self->ListDocumentClassifiers(@_, NextToken => $result->NextToken); } $callback->($_ => 'DocumentClassifierPropertiesList') foreach (@{ $result->DocumentClassifierPropertiesList }); } return undef } sub ListAllDominantLanguageDetectionJobs { my $self = shift; my $callback = shift @_ if (ref($_[0]) eq 'CODE'); my $result = $self->ListDominantLanguageDetectionJobs(@_); my $next_result = $result; if (not defined $callback) { while ($next_result->NextToken) { $next_result = $self->ListDominantLanguageDetectionJobs(@_, NextToken => $next_result->NextToken); push @{ $result->DominantLanguageDetectionJobPropertiesList }, @{ $next_result->DominantLanguageDetectionJobPropertiesList }; } return $result; } else { while ($result->NextToken) { $callback->($_ => 'DominantLanguageDetectionJobPropertiesList') foreach (@{ $result->DominantLanguageDetectionJobPropertiesList }); $result = $self->ListDominantLanguageDetectionJobs(@_, NextToken => $result->NextToken); } $callback->($_ => 'DominantLanguageDetectionJobPropertiesList') foreach (@{ $result->DominantLanguageDetectionJobPropertiesList }); } return undef } sub ListAllEntitiesDetectionJobs { my $self = shift; my $callback = shift @_ if (ref($_[0]) eq 'CODE'); my $result = $self->ListEntitiesDetectionJobs(@_); my $next_result = $result; if (not defined $callback) { while ($next_result->NextToken) { $next_result = $self->ListEntitiesDetectionJobs(@_, NextToken => $next_result->NextToken); push @{ $result->EntitiesDetectionJobPropertiesList }, @{ $next_result->EntitiesDetectionJobPropertiesList }; } return $result; } else { while ($result->NextToken) { $callback->($_ => 'EntitiesDetectionJobPropertiesList') foreach (@{ $result->EntitiesDetectionJobPropertiesList }); $result = $self->ListEntitiesDetectionJobs(@_, NextToken => $result->NextToken); } $callback->($_ => 'EntitiesDetectionJobPropertiesList') foreach (@{ $result->EntitiesDetectionJobPropertiesList }); } return undef } sub ListAllEntityRecognizers { my $self = shift; my $callback = shift @_ if (ref($_[0]) eq 'CODE'); my $result = $self->ListEntityRecognizers(@_); my $next_result = $result; if (not defined $callback) { while ($next_result->NextToken) { $next_result = $self->ListEntityRecognizers(@_, NextToken => $next_result->NextToken); push @{ $result->EntityRecognizerPropertiesList }, @{ $next_result->EntityRecognizerPropertiesList }; } return $result; } else { while ($result->NextToken) { $callback->($_ => 'EntityRecognizerPropertiesList') foreach (@{ $result->EntityRecognizerPropertiesList }); $result = $self->ListEntityRecognizers(@_, NextToken => $result->NextToken); } $callback->($_ => 'EntityRecognizerPropertiesList') foreach (@{ $result->EntityRecognizerPropertiesList }); } return undef } sub ListAllKeyPhrasesDetectionJobs { my $self = shift; my $callback = shift @_ if (ref($_[0]) eq 'CODE'); my $result = $self->ListKeyPhrasesDetectionJobs(@_); my $next_result = $result; if (not defined $callback) { while ($next_result->NextToken) { $next_result = $self->ListKeyPhrasesDetectionJobs(@_, NextToken => $next_result->NextToken); push @{ $result->KeyPhrasesDetectionJobPropertiesList }, @{ $next_result->KeyPhrasesDetectionJobPropertiesList }; } return $result; } else { while ($result->NextToken) { $callback->($_ => 'KeyPhrasesDetectionJobPropertiesList') foreach (@{ $result->KeyPhrasesDetectionJobPropertiesList }); $result = $self->ListKeyPhrasesDetectionJobs(@_, NextToken => $result->NextToken); } $callback->($_ => 'KeyPhrasesDetectionJobPropertiesList') foreach (@{ $result->KeyPhrasesDetectionJobPropertiesList }); } return undef } sub ListAllSentimentDetectionJobs { my $self = shift; my $callback = shift @_ if (ref($_[0]) eq 'CODE'); my $result = $self->ListSentimentDetectionJobs(@_); my $next_result = $result; if (not defined $callback) { while ($next_result->NextToken) { $next_result = $self->ListSentimentDetectionJobs(@_, NextToken => $next_result->NextToken); push @{ $result->SentimentDetectionJobPropertiesList }, @{ $next_result->SentimentDetectionJobPropertiesList }; } return $result; } else { while ($result->NextToken) { $callback->($_ => 'SentimentDetectionJobPropertiesList') foreach (@{ $result->SentimentDetectionJobPropertiesList }); $result = $self->ListSentimentDetectionJobs(@_, NextToken => $result->NextToken); } $callback->($_ => 'SentimentDetectionJobPropertiesList') foreach (@{ $result->SentimentDetectionJobPropertiesList }); } return undef } sub ListAllTopicsDetectionJobs { my $self = shift; my $callback = shift @_ if (ref($_[0]) eq 'CODE'); my $result = $self->ListTopicsDetectionJobs(@_); my $next_result = $result; if (not defined $callback) { while ($next_result->NextToken) { $next_result = $self->ListTopicsDetectionJobs(@_, NextToken => $next_result->NextToken); push @{ $result->TopicsDetectionJobPropertiesList }, @{ $next_result->TopicsDetectionJobPropertiesList }; } return $result; } else { while ($result->NextToken) { $callback->($_ => 'TopicsDetectionJobPropertiesList') foreach (@{ $result->TopicsDetectionJobPropertiesList }); $result = $self->ListTopicsDetectionJobs(@_, NextToken => $result->NextToken); } $callback->($_ => 'TopicsDetectionJobPropertiesList') foreach (@{ $result->TopicsDetectionJobPropertiesList }); } return undef } sub operations { qw/BatchDetectDominantLanguage BatchDetectEntities BatchDetectKeyPhrases BatchDetectSentiment BatchDetectSyntax ClassifyDocument ContainsPiiEntities CreateDocumentClassifier CreateEndpoint CreateEntityRecognizer DeleteDocumentClassifier DeleteEndpoint DeleteEntityRecognizer DescribeDocumentClassificationJob DescribeDocumentClassifier DescribeDominantLanguageDetectionJob DescribeEndpoint DescribeEntitiesDetectionJob DescribeEntityRecognizer DescribeEventsDetectionJob DescribeKeyPhrasesDetectionJob DescribePiiEntitiesDetectionJob DescribeSentimentDetectionJob DescribeTopicsDetectionJob DetectDominantLanguage DetectEntities DetectKeyPhrases DetectPiiEntities DetectSentiment DetectSyntax ListDocumentClassificationJobs ListDocumentClassifiers ListDominantLanguageDetectionJobs ListEndpoints ListEntitiesDetectionJobs ListEntityRecognizers ListEventsDetectionJobs ListKeyPhrasesDetectionJobs ListPiiEntitiesDetectionJobs ListSentimentDetectionJobs ListTagsForResource ListTopicsDetectionJobs StartDocumentClassificationJob StartDominantLanguageDetectionJob StartEntitiesDetectionJob StartEventsDetectionJob StartKeyPhrasesDetectionJob StartPiiEntitiesDetectionJob StartSentimentDetectionJob StartTopicsDetectionJob StopDominantLanguageDetectionJob StopEntitiesDetectionJob StopEventsDetectionJob StopKeyPhrasesDetectionJob StopPiiEntitiesDetectionJob StopSentimentDetectionJob StopTrainingDocumentClassifier StopTrainingEntityRecognizer TagResource UntagResource UpdateEndpoint / } 1; ### main pod documentation begin ### =head1 NAME Paws::Comprehend - Perl Interface to AWS Amazon Comprehend =head1 SYNOPSIS use Paws; my $obj = Paws->service('Comprehend'); my $res = $obj->Method( Arg1 => $val1, Arg2 => [ 'V1', 'V2' ], # if Arg3 is an object, the HashRef will be used as arguments to the constructor # of the arguments type Arg3 => { Att1 => 'Val1' }, # if Arg4 is an array of objects, the HashRefs will be passed as arguments to # the constructor of the arguments type Arg4 => [ { Att1 => 'Val1' }, { Att1 => 'Val2' } ], ); =head1 DESCRIPTION Amazon Comprehend is an AWS service for gaining insight into the content of documents. Use these actions to determine the topics contained in your documents, the topics they discuss, the predominant sentiment expressed in them, the predominant language used, and more. For the AWS API documentation, see L =head1 METHODS =head2 BatchDetectDominantLanguage =over =item TextList => ArrayRef[Str|Undef] =back Each argument is described in detail in: L Returns: a L instance Determines the dominant language of the input text for a batch of documents. For a list of languages that Amazon Comprehend can detect, see Amazon Comprehend Supported Languages (https://docs.aws.amazon.com/comprehend/latest/dg/how-languages.html). =head2 BatchDetectEntities =over =item LanguageCode => Str =item TextList => ArrayRef[Str|Undef] =back Each argument is described in detail in: L Returns: a L instance Inspects the text of a batch of documents for named entities and returns information about them. For more information about named entities, see how-entities =head2 BatchDetectKeyPhrases =over =item LanguageCode => Str =item TextList => ArrayRef[Str|Undef] =back Each argument is described in detail in: L Returns: a L instance Detects the key noun phrases found in a batch of documents. =head2 BatchDetectSentiment =over =item LanguageCode => Str =item TextList => ArrayRef[Str|Undef] =back Each argument is described in detail in: L Returns: a L instance Inspects a batch of documents and returns an inference of the prevailing sentiment, C, C, C, or C, in each one. =head2 BatchDetectSyntax =over =item LanguageCode => Str =item TextList => ArrayRef[Str|Undef] =back Each argument is described in detail in: L Returns: a L instance Inspects the text of a batch of documents for the syntax and part of speech of the words in the document and returns information about them. For more information, see how-syntax. =head2 ClassifyDocument =over =item EndpointArn => Str =item Text => Str =back Each argument is described in detail in: L Returns: a L instance Creates a new document classification request to analyze a single document in real-time, using a previously created and trained custom model and an endpoint. =head2 ContainsPiiEntities =over =item LanguageCode => Str =item Text => Str =back Each argument is described in detail in: L Returns: a L instance Analyzes input text for the presence of personally identifiable information (PII) and returns the labels of identified PII entity types such as name, address, bank account number, or phone number. =head2 CreateDocumentClassifier =over =item DataAccessRoleArn => Str =item DocumentClassifierName => Str =item InputDataConfig => L =item LanguageCode => Str =item [ClientRequestToken => Str] =item [Mode => Str] =item [ModelKmsKeyId => Str] =item [OutputDataConfig => L] =item [Tags => ArrayRef[L]] =item [VolumeKmsKeyId => Str] =item [VpcConfig => L] =back Each argument is described in detail in: L Returns: a L instance Creates a new document classifier that you can use to categorize documents. To create a classifier, you provide a set of training documents that labeled with the categories that you want to use. After the classifier is trained you can use it to categorize a set of labeled documents into the categories. For more information, see how-document-classification. =head2 CreateEndpoint =over =item DesiredInferenceUnits => Int =item EndpointName => Str =item ModelArn => Str =item [ClientRequestToken => Str] =item [DataAccessRoleArn => Str] =item [Tags => ArrayRef[L]] =back Each argument is described in detail in: L Returns: a L instance Creates a model-specific endpoint for synchronous inference for a previously trained custom model =head2 CreateEntityRecognizer =over =item DataAccessRoleArn => Str =item InputDataConfig => L =item LanguageCode => Str =item RecognizerName => Str =item [ClientRequestToken => Str] =item [ModelKmsKeyId => Str] =item [Tags => ArrayRef[L]] =item [VolumeKmsKeyId => Str] =item [VpcConfig => L] =back Each argument is described in detail in: L Returns: a L instance Creates an entity recognizer using submitted files. After your C request is submitted, you can check job status using the API. =head2 DeleteDocumentClassifier =over =item DocumentClassifierArn => Str =back Each argument is described in detail in: L Returns: a L instance Deletes a previously created document classifier Only those classifiers that are in terminated states (IN_ERROR, TRAINED) will be deleted. If an active inference job is using the model, a C will be returned. This is an asynchronous action that puts the classifier into a DELETING state, and it is then removed by a background job. Once removed, the classifier disappears from your account and is no longer available for use. =head2 DeleteEndpoint =over =item EndpointArn => Str =back Each argument is described in detail in: L Returns: a L instance Deletes a model-specific endpoint for a previously-trained custom model. All endpoints must be deleted in order for the model to be deleted. =head2 DeleteEntityRecognizer =over =item EntityRecognizerArn => Str =back Each argument is described in detail in: L Returns: a L instance Deletes an entity recognizer. Only those recognizers that are in terminated states (IN_ERROR, TRAINED) will be deleted. If an active inference job is using the model, a C will be returned. This is an asynchronous action that puts the recognizer into a DELETING state, and it is then removed by a background job. Once removed, the recognizer disappears from your account and is no longer available for use. =head2 DescribeDocumentClassificationJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Gets the properties associated with a document classification job. Use this operation to get the status of a classification job. =head2 DescribeDocumentClassifier =over =item DocumentClassifierArn => Str =back Each argument is described in detail in: L Returns: a L instance Gets the properties associated with a document classifier. =head2 DescribeDominantLanguageDetectionJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Gets the properties associated with a dominant language detection job. Use this operation to get the status of a detection job. =head2 DescribeEndpoint =over =item EndpointArn => Str =back Each argument is described in detail in: L Returns: a L instance Gets the properties associated with a specific endpoint. Use this operation to get the status of an endpoint. =head2 DescribeEntitiesDetectionJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Gets the properties associated with an entities detection job. Use this operation to get the status of a detection job. =head2 DescribeEntityRecognizer =over =item EntityRecognizerArn => Str =back Each argument is described in detail in: L Returns: a L instance Provides details about an entity recognizer including status, S3 buckets containing training data, recognizer metadata, metrics, and so on. =head2 DescribeEventsDetectionJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Gets the status and details of an events detection job. =head2 DescribeKeyPhrasesDetectionJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Gets the properties associated with a key phrases detection job. Use this operation to get the status of a detection job. =head2 DescribePiiEntitiesDetectionJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Gets the properties associated with a PII entities detection job. For example, you can use this operation to get the job status. =head2 DescribeSentimentDetectionJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Gets the properties associated with a sentiment detection job. Use this operation to get the status of a detection job. =head2 DescribeTopicsDetectionJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Gets the properties associated with a topic detection job. Use this operation to get the status of a detection job. =head2 DetectDominantLanguage =over =item Text => Str =back Each argument is described in detail in: L Returns: a L instance Determines the dominant language of the input text. For a list of languages that Amazon Comprehend can detect, see Amazon Comprehend Supported Languages (https://docs.aws.amazon.com/comprehend/latest/dg/how-languages.html). =head2 DetectEntities =over =item Text => Str =item [EndpointArn => Str] =item [LanguageCode => Str] =back Each argument is described in detail in: L Returns: a L instance Inspects text for named entities, and returns information about them. For more information, about named entities, see how-entities. =head2 DetectKeyPhrases =over =item LanguageCode => Str =item Text => Str =back Each argument is described in detail in: L Returns: a L instance Detects the key noun phrases found in the text. =head2 DetectPiiEntities =over =item LanguageCode => Str =item Text => Str =back Each argument is described in detail in: L Returns: a L instance Inspects the input text for entities that contain personally identifiable information (PII) and returns information about them. =head2 DetectSentiment =over =item LanguageCode => Str =item Text => Str =back Each argument is described in detail in: L Returns: a L instance Inspects text and returns an inference of the prevailing sentiment (C, C, C, or C). =head2 DetectSyntax =over =item LanguageCode => Str =item Text => Str =back Each argument is described in detail in: L Returns: a L instance Inspects text for syntax and the part of speech of words in the document. For more information, how-syntax. =head2 ListDocumentClassificationJobs =over =item [Filter => L] =item [MaxResults => Int] =item [NextToken => Str] =back Each argument is described in detail in: L Returns: a L instance Gets a list of the documentation classification jobs that you have submitted. =head2 ListDocumentClassifiers =over =item [Filter => L] =item [MaxResults => Int] =item [NextToken => Str] =back Each argument is described in detail in: L Returns: a L instance Gets a list of the document classifiers that you have created. =head2 ListDominantLanguageDetectionJobs =over =item [Filter => L] =item [MaxResults => Int] =item [NextToken => Str] =back Each argument is described in detail in: L Returns: a L instance Gets a list of the dominant language detection jobs that you have submitted. =head2 ListEndpoints =over =item [Filter => L] =item [MaxResults => Int] =item [NextToken => Str] =back Each argument is described in detail in: L Returns: a L instance Gets a list of all existing endpoints that you've created. =head2 ListEntitiesDetectionJobs =over =item [Filter => L] =item [MaxResults => Int] =item [NextToken => Str] =back Each argument is described in detail in: L Returns: a L instance Gets a list of the entity detection jobs that you have submitted. =head2 ListEntityRecognizers =over =item [Filter => L] =item [MaxResults => Int] =item [NextToken => Str] =back Each argument is described in detail in: L Returns: a L instance Gets a list of the properties of all entity recognizers that you created, including recognizers currently in training. Allows you to filter the list of recognizers based on criteria such as status and submission time. This call returns up to 500 entity recognizers in the list, with a default number of 100 recognizers in the list. The results of this list are not in any particular order. Please get the list and sort locally if needed. =head2 ListEventsDetectionJobs =over =item [Filter => L] =item [MaxResults => Int] =item [NextToken => Str] =back Each argument is described in detail in: L Returns: a L instance Gets a list of the events detection jobs that you have submitted. =head2 ListKeyPhrasesDetectionJobs =over =item [Filter => L] =item [MaxResults => Int] =item [NextToken => Str] =back Each argument is described in detail in: L Returns: a L instance Get a list of key phrase detection jobs that you have submitted. =head2 ListPiiEntitiesDetectionJobs =over =item [Filter => L] =item [MaxResults => Int] =item [NextToken => Str] =back Each argument is described in detail in: L Returns: a L instance Gets a list of the PII entity detection jobs that you have submitted. =head2 ListSentimentDetectionJobs =over =item [Filter => L] =item [MaxResults => Int] =item [NextToken => Str] =back Each argument is described in detail in: L Returns: a L instance Gets a list of sentiment detection jobs that you have submitted. =head2 ListTagsForResource =over =item ResourceArn => Str =back Each argument is described in detail in: L Returns: a L instance Lists all tags associated with a given Amazon Comprehend resource. =head2 ListTopicsDetectionJobs =over =item [Filter => L] =item [MaxResults => Int] =item [NextToken => Str] =back Each argument is described in detail in: L Returns: a L instance Gets a list of the topic detection jobs that you have submitted. =head2 StartDocumentClassificationJob =over =item DataAccessRoleArn => Str =item DocumentClassifierArn => Str =item InputDataConfig => L =item OutputDataConfig => L =item [ClientRequestToken => Str] =item [JobName => Str] =item [VolumeKmsKeyId => Str] =item [VpcConfig => L] =back Each argument is described in detail in: L Returns: a L instance Starts an asynchronous document classification job. Use the operation to track the progress of the job. =head2 StartDominantLanguageDetectionJob =over =item DataAccessRoleArn => Str =item InputDataConfig => L =item OutputDataConfig => L =item [ClientRequestToken => Str] =item [JobName => Str] =item [VolumeKmsKeyId => Str] =item [VpcConfig => L] =back Each argument is described in detail in: L Returns: a L instance Starts an asynchronous dominant language detection job for a collection of documents. Use the operation to track the status of a job. =head2 StartEntitiesDetectionJob =over =item DataAccessRoleArn => Str =item InputDataConfig => L =item LanguageCode => Str =item OutputDataConfig => L =item [ClientRequestToken => Str] =item [EntityRecognizerArn => Str] =item [JobName => Str] =item [VolumeKmsKeyId => Str] =item [VpcConfig => L] =back Each argument is described in detail in: L Returns: a L instance Starts an asynchronous entity detection job for a collection of documents. Use the operation to track the status of a job. This API can be used for either standard entity detection or custom entity recognition. In order to be used for custom entity recognition, the optional C must be used in order to provide access to the recognizer being used to detect the custom entity. =head2 StartEventsDetectionJob =over =item DataAccessRoleArn => Str =item InputDataConfig => L =item LanguageCode => Str =item OutputDataConfig => L =item TargetEventTypes => ArrayRef[Str|Undef] =item [ClientRequestToken => Str] =item [JobName => Str] =back Each argument is described in detail in: L Returns: a L instance Starts an asynchronous event detection job for a collection of documents. =head2 StartKeyPhrasesDetectionJob =over =item DataAccessRoleArn => Str =item InputDataConfig => L =item LanguageCode => Str =item OutputDataConfig => L =item [ClientRequestToken => Str] =item [JobName => Str] =item [VolumeKmsKeyId => Str] =item [VpcConfig => L] =back Each argument is described in detail in: L Returns: a L instance Starts an asynchronous key phrase detection job for a collection of documents. Use the operation to track the status of a job. =head2 StartPiiEntitiesDetectionJob =over =item DataAccessRoleArn => Str =item InputDataConfig => L =item LanguageCode => Str =item Mode => Str =item OutputDataConfig => L =item [ClientRequestToken => Str] =item [JobName => Str] =item [RedactionConfig => L] =back Each argument is described in detail in: L Returns: a L instance Starts an asynchronous PII entity detection job for a collection of documents. =head2 StartSentimentDetectionJob =over =item DataAccessRoleArn => Str =item InputDataConfig => L =item LanguageCode => Str =item OutputDataConfig => L =item [ClientRequestToken => Str] =item [JobName => Str] =item [VolumeKmsKeyId => Str] =item [VpcConfig => L] =back Each argument is described in detail in: L Returns: a L instance Starts an asynchronous sentiment detection job for a collection of documents. use the operation to track the status of a job. =head2 StartTopicsDetectionJob =over =item DataAccessRoleArn => Str =item InputDataConfig => L =item OutputDataConfig => L =item [ClientRequestToken => Str] =item [JobName => Str] =item [NumberOfTopics => Int] =item [VolumeKmsKeyId => Str] =item [VpcConfig => L] =back Each argument is described in detail in: L Returns: a L instance Starts an asynchronous topic detection job. Use the C operation to track the status of a job. =head2 StopDominantLanguageDetectionJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Stops a dominant language detection job in progress. If the job state is C the job is marked for termination and put into the C state. If the job completes before it can be stopped, it is put into the C state; otherwise the job is stopped and put into the C state. If the job is in the C or C state when you call the C operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location. =head2 StopEntitiesDetectionJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Stops an entities detection job in progress. If the job state is C the job is marked for termination and put into the C state. If the job completes before it can be stopped, it is put into the C state; otherwise the job is stopped and put into the C state. If the job is in the C or C state when you call the C operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location. =head2 StopEventsDetectionJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Stops an events detection job in progress. =head2 StopKeyPhrasesDetectionJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Stops a key phrases detection job in progress. If the job state is C the job is marked for termination and put into the C state. If the job completes before it can be stopped, it is put into the C state; otherwise the job is stopped and put into the C state. If the job is in the C or C state when you call the C operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location. =head2 StopPiiEntitiesDetectionJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Stops a PII entities detection job in progress. =head2 StopSentimentDetectionJob =over =item JobId => Str =back Each argument is described in detail in: L Returns: a L instance Stops a sentiment detection job in progress. If the job state is C the job is marked for termination and put into the C state. If the job completes before it can be stopped, it is put into the C state; otherwise the job is be stopped and put into the C state. If the job is in the C or C state when you call the C operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location. =head2 StopTrainingDocumentClassifier =over =item DocumentClassifierArn => Str =back Each argument is described in detail in: L Returns: a L instance Stops a document classifier training job while in progress. If the training job state is C, the job is marked for termination and put into the C state. If the training job completes before it can be stopped, it is put into the C; otherwise the training job is stopped and put into the C state and the service sends back an HTTP 200 response with an empty HTTP body. =head2 StopTrainingEntityRecognizer =over =item EntityRecognizerArn => Str =back Each argument is described in detail in: L Returns: a L instance Stops an entity recognizer training job while in progress. If the training job state is C, the job is marked for termination and put into the C state. If the training job completes before it can be stopped, it is put into the C; otherwise the training job is stopped and putted into the C state and the service sends back an HTTP 200 response with an empty HTTP body. =head2 TagResource =over =item ResourceArn => Str =item Tags => ArrayRef[L] =back Each argument is described in detail in: L Returns: a L instance Associates a specific tag with an Amazon Comprehend resource. A tag is a key-value pair that adds as a 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. =head2 UntagResource =over =item ResourceArn => Str =item TagKeys => ArrayRef[Str|Undef] =back Each argument is described in detail in: L Returns: a L instance Removes a specific tag associated with an Amazon Comprehend resource. =head2 UpdateEndpoint =over =item DesiredInferenceUnits => Int =item EndpointArn => Str =back Each argument is described in detail in: L Returns: a L instance Updates information about the specified endpoint. =head1 PAGINATORS Paginator methods are helpers that repetively call methods that return partial results =head2 ListAllDocumentClassificationJobs(sub { },[Filter => L, MaxResults => Int, NextToken => Str]) =head2 ListAllDocumentClassificationJobs([Filter => L, MaxResults => Int, NextToken => Str]) If passed a sub as first parameter, it will call the sub for each element found in : - DocumentClassificationJobPropertiesList, passing the object as the first parameter, and the string 'DocumentClassificationJobPropertiesList' as the second parameter If not, it will return a a L instance with all the Cs; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory. =head2 ListAllDocumentClassifiers(sub { },[Filter => L, MaxResults => Int, NextToken => Str]) =head2 ListAllDocumentClassifiers([Filter => L, MaxResults => Int, NextToken => Str]) If passed a sub as first parameter, it will call the sub for each element found in : - DocumentClassifierPropertiesList, passing the object as the first parameter, and the string 'DocumentClassifierPropertiesList' as the second parameter If not, it will return a a L instance with all the Cs; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory. =head2 ListAllDominantLanguageDetectionJobs(sub { },[Filter => L, MaxResults => Int, NextToken => Str]) =head2 ListAllDominantLanguageDetectionJobs([Filter => L, MaxResults => Int, NextToken => Str]) If passed a sub as first parameter, it will call the sub for each element found in : - DominantLanguageDetectionJobPropertiesList, passing the object as the first parameter, and the string 'DominantLanguageDetectionJobPropertiesList' as the second parameter If not, it will return a a L instance with all the Cs; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory. =head2 ListAllEntitiesDetectionJobs(sub { },[Filter => L, MaxResults => Int, NextToken => Str]) =head2 ListAllEntitiesDetectionJobs([Filter => L, MaxResults => Int, NextToken => Str]) If passed a sub as first parameter, it will call the sub for each element found in : - EntitiesDetectionJobPropertiesList, passing the object as the first parameter, and the string 'EntitiesDetectionJobPropertiesList' as the second parameter If not, it will return a a L instance with all the Cs; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory. =head2 ListAllEntityRecognizers(sub { },[Filter => L, MaxResults => Int, NextToken => Str]) =head2 ListAllEntityRecognizers([Filter => L, MaxResults => Int, NextToken => Str]) If passed a sub as first parameter, it will call the sub for each element found in : - EntityRecognizerPropertiesList, passing the object as the first parameter, and the string 'EntityRecognizerPropertiesList' as the second parameter If not, it will return a a L instance with all the Cs; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory. =head2 ListAllKeyPhrasesDetectionJobs(sub { },[Filter => L, MaxResults => Int, NextToken => Str]) =head2 ListAllKeyPhrasesDetectionJobs([Filter => L, MaxResults => Int, NextToken => Str]) If passed a sub as first parameter, it will call the sub for each element found in : - KeyPhrasesDetectionJobPropertiesList, passing the object as the first parameter, and the string 'KeyPhrasesDetectionJobPropertiesList' as the second parameter If not, it will return a a L instance with all the Cs; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory. =head2 ListAllSentimentDetectionJobs(sub { },[Filter => L, MaxResults => Int, NextToken => Str]) =head2 ListAllSentimentDetectionJobs([Filter => L, MaxResults => Int, NextToken => Str]) If passed a sub as first parameter, it will call the sub for each element found in : - SentimentDetectionJobPropertiesList, passing the object as the first parameter, and the string 'SentimentDetectionJobPropertiesList' as the second parameter If not, it will return a a L instance with all the Cs; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory. =head2 ListAllTopicsDetectionJobs(sub { },[Filter => L, MaxResults => Int, NextToken => Str]) =head2 ListAllTopicsDetectionJobs([Filter => L, MaxResults => Int, NextToken => Str]) If passed a sub as first parameter, it will call the sub for each element found in : - TopicsDetectionJobPropertiesList, passing the object as the first parameter, and the string 'TopicsDetectionJobPropertiesList' as the second parameter If not, it will return a a L instance with all the Cs; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory. =head1 SEE ALSO This service class forms part of L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut