Module types

Data structures used by operation inputs/outputs.

Modules

builders

Builders

error

Error types that Amazon Comprehend can respond with.

Structs

AugmentedManifestsListItem

An augmented manifest file that provides training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.

BatchDetectDominantLanguageItemResult

The result of calling the operation. The operation returns one object for each document that is successfully processed by the operation.

BatchDetectEntitiesItemResult

The result of calling the operation. The operation returns one object for each document that is successfully processed by the operation.

BatchDetectKeyPhrasesItemResult

The result of calling the operation. The operation returns one object for each document that is successfully processed by the operation.

BatchDetectSentimentItemResult

The result of calling the operation. The operation returns one object for each document that is successfully processed by the operation.

BatchDetectSyntaxItemResult

The result of calling the operation. The operation returns one object that is successfully processed by the operation.

BatchDetectTargetedSentimentItemResult

Analysis results for one of the documents in the batch.

BatchItemError

Describes an error that occurred while processing a document in a batch. The operation returns on BatchItemError object for each document that contained an error.

Block

Information about each word or line of text in the input document.

For additional information, see Block in the Amazon Textract API reference.

BlockReference

A reference to a block.

BoundingBox

The bounding box around the detected page or around an element on a document page. The left (x-coordinate) and top (y-coordinate) are coordinates that represent the top and left sides of the bounding box. Note that the upper-left corner of the image is the origin (0,0).

For additional information, see BoundingBox in the Amazon Textract API reference.

ChildBlock

Nested block contained within a block.

ClassifierEvaluationMetrics

Describes the result metrics for the test data associated with an documentation classifier.

ClassifierMetadata

Provides information about a document classifier.

DataSecurityConfig

Data security configuration.

DatasetAugmentedManifestsListItem

An augmented manifest file that provides training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.

DatasetDocumentClassifierInputDataConfig

Describes the dataset input data configuration for a document classifier model.

For more information on how the input file is formatted, see Preparing training data in the Comprehend Developer Guide.

DatasetEntityRecognizerAnnotations

Describes the annotations associated with a entity recognizer.

DatasetEntityRecognizerDocuments

Describes the documents submitted with a dataset for an entity recognizer model.

DatasetEntityRecognizerEntityList

Describes the dataset entity list for an entity recognizer model.

For more information on how the input file is formatted, see Preparing training data in the Comprehend Developer Guide.

DatasetEntityRecognizerInputDataConfig

Specifies the format and location of the input data. You must provide either the Annotations parameter or the EntityList parameter.

DatasetFilter

Filter the datasets based on creation time or dataset status.

DatasetInputDataConfig

Specifies the format and location of the input data for the dataset.

DatasetProperties

Properties associated with the dataset.

DocumentClass

Specifies the class that categorizes the document being analyzed

DocumentClassificationConfig

Configuration required for a document classification model.

DocumentClassificationJobFilter

Provides information for filtering a list of document classification jobs. For more information, see the operation. You can provide only one filter parameter in each request.

DocumentClassificationJobProperties

Provides information about a document classification job.

DocumentClassifierDocuments

The location of the training documents. This parameter is required in a request to create a semi-structured document classification model.

DocumentClassifierFilter

Provides information for filtering a list of document classifiers. You can only specify one filtering parameter in a request. For more information, see the ListDocumentClassifiers operation.

DocumentClassifierInputDataConfig

The input properties for training a document classifier.

For more information on how the input file is formatted, see Preparing training data in the Comprehend Developer Guide.

DocumentClassifierOutputDataConfig

Provide the location for output data from a custom classifier job. This field is mandatory if you are training a native document model.

DocumentClassifierProperties

Provides information about a document classifier.

DocumentClassifierSummary

Describes information about a document classifier and its versions.

DocumentLabel

Specifies one of the label or labels that categorize the document being analyzed.

DocumentMetadata

Information about the document, discovered during text extraction.

DocumentReaderConfig

Provides configuration parameters to override the default actions for extracting text from PDF documents and image files.

By default, Amazon Comprehend performs the following actions to extract text from files, based on the input file type:

• Word files - Amazon Comprehend parser extracts the text.

• Digital PDF files - Amazon Comprehend parser extracts the text.

• Image files and scanned PDF files - Amazon Comprehend uses the Amazon Textract DetectDocumentText API to extract the text.

DocumentReaderConfig does not apply to plain text files or Word files.

For image files and PDF documents, you can override these default actions using the fields listed below. For more information, see Setting text extraction options in the Comprehend Developer Guide.

DocumentTypeListItem

Document type for each page in the document.

DominantLanguage

Returns the code for the dominant language in the input text and the level of confidence that Amazon Comprehend has in the accuracy of the detection.

DominantLanguageDetectionJobFilter

Provides information for filtering a list of dominant language detection jobs. For more information, see the operation.

DominantLanguageDetectionJobProperties

Provides information about a dominant language detection job.

EndpointFilter

The filter used to determine which endpoints are returned. You can filter jobs on their name, model, status, or the date and time that they were created. You can only set one filter at a time.

EndpointProperties

Specifies information about the specified endpoint. For information about endpoints, see Managing endpoints.

EntitiesDetectionJobFilter

Provides information for filtering a list of dominant language detection jobs. For more information, see the operation.

EntitiesDetectionJobProperties

Provides information about an entities detection job.

Entity

Provides information about an entity.

EntityLabel

Specifies one of the label or labels that categorize the personally identifiable information (PII) entity being analyzed.

EntityRecognitionConfig

Configuration required for an entity recognition model.

EntityRecognizerAnnotations

Describes the annotations associated with a entity recognizer.

EntityRecognizerDocuments

Describes the training documents submitted with an entity recognizer.

EntityRecognizerEntityList

Describes the entity list submitted with an entity recognizer.

EntityRecognizerEvaluationMetrics

Detailed information about the accuracy of an entity recognizer.

EntityRecognizerFilter

Provides information for filtering a list of entity recognizers. You can only specify one filtering parameter in a request. For more information, see the ListEntityRecognizers operation./>

EntityRecognizerInputDataConfig

Specifies the format and location of the input data.

EntityRecognizerMetadata

Detailed information about an entity recognizer.

EntityRecognizerMetadataEntityTypesListItem

Individual item from the list of entity types in the metadata of an entity recognizer.

EntityRecognizerOutputDataConfig

Output data configuration.

EntityRecognizerProperties

Describes information about an entity recognizer.

EntityRecognizerSummary

Describes the information about an entity recognizer and its versions.

EntityTypesEvaluationMetrics

Detailed information about the accuracy of an entity recognizer for a specific entity type.

EntityTypesListItem

An entity type within a labeled training dataset that Amazon Comprehend uses to train a custom entity recognizer.

ErrorsListItem

Text extraction encountered one or more page-level errors in the input document.

The ErrorCode contains one of the following values:

• TEXTRACT_BAD_PAGE - Amazon Textract cannot read the page. For more information about page limits in Amazon Textract, see Page Quotas in Amazon Textract.

• TEXTRACT_PROVISIONED_THROUGHPUT_EXCEEDED - The number of requests exceeded your throughput limit. For more information about throughput quotas in Amazon Textract, see Default quotas in Amazon Textract.

• PAGE_CHARACTERS_EXCEEDED - Too many text characters on the page (10,000 characters maximum).

• PAGE_SIZE_EXCEEDED - The maximum page size is 10 MB.

• INTERNAL_SERVER_ERROR - The request encountered a service issue. Try the API request again.

EventsDetectionJobFilter

Provides information for filtering a list of event detection jobs.

EventsDetectionJobProperties

Provides information about an events detection job.

ExtractedCharactersListItem

Array of the number of characters extracted from each page.

FlywheelFilter

Filter the flywheels based on creation time or flywheel status.

FlywheelIterationFilter

Filter the flywheel iterations based on creation time.

FlywheelIterationProperties

The configuration properties of a flywheel iteration.

FlywheelModelEvaluationMetrics

The evaluation metrics associated with the evaluated model.

FlywheelProperties

The flywheel properties.

FlywheelSummary

Flywheel summary information.

Geometry

Information about the location of items on a document page.

For additional information, see Geometry in the Amazon Textract API reference.

InputDataConfig

The input properties for an inference job. The document reader config field applies only to non-text inputs for custom analysis.

InvalidRequestDetail

Provides additional detail about why the request failed.

KeyPhrase

Describes a key noun phrase.

KeyPhrasesDetectionJobFilter

Provides information for filtering a list of dominant language detection jobs. For more information, see the operation.

KeyPhrasesDetectionJobProperties

Provides information about a key phrases detection job.

MentionSentiment

Contains the sentiment and sentiment score for one mention of an entity.

For more information about targeted sentiment, see Targeted sentiment in the Amazon Comprehend Developer Guide.

OutputDataConfig

Provides configuration parameters for the output of inference jobs.

PartOfSpeechTag

Identifies the part of speech represented by the token and gives the confidence that Amazon Comprehend has that the part of speech was correctly identified. For more information about the parts of speech that Amazon Comprehend can identify, see Syntax in the Comprehend Developer Guide.

PiiEntitiesDetectionJobFilter

Provides information for filtering a list of PII entity detection jobs.

PiiEntitiesDetectionJobProperties

Provides information about a PII entities detection job.

PiiEntity

Provides information about a PII entity.

PiiOutputDataConfig

Provides configuration parameters for the output of PII entity detection jobs.

Point

The X and Y coordinates of a point on a document page.

For additional information, see Point in the Amazon Textract API reference.

RedactionConfig

Provides configuration parameters for PII entity redaction.

RelationshipsListItem

List of child blocks for the current block.

SentimentDetectionJobFilter

Provides information for filtering a list of dominant language detection jobs. For more information, see the operation.

SentimentDetectionJobProperties

Provides information about a sentiment detection job.

SentimentScore

Describes the level of confidence that Amazon Comprehend has in the accuracy of its detection of sentiments.

SyntaxToken

Represents a work in the input text that was recognized and assigned a part of speech. There is one syntax token record for each word in the source text.

Tag

A key-value pair that adds as a metadata to a resource used by Amazon Comprehend. For example, a tag with the key-value pair ‘Department’:’Sales’ might be added to a resource to indicate its use by a particular department.

TargetedSentimentDetectionJobFilter

Provides information for filtering a list of dominant language detection jobs. For more information, see the ListTargetedSentimentDetectionJobs operation.

TargetedSentimentDetectionJobProperties

Provides information about a targeted sentiment detection job.

TargetedSentimentEntity

Information about one of the entities found by targeted sentiment analysis.

For more information about targeted sentiment, see Targeted sentiment in the Amazon Comprehend Developer Guide.

TargetedSentimentMention

Information about one mention of an entity. The mention information includes the location of the mention in the text and the sentiment of the mention.

For more information about targeted sentiment, see Targeted sentiment in the Amazon Comprehend Developer Guide.

TaskConfig

Configuration about the model associated with a flywheel.

TextSegment

One of the of text strings. Each string has a size limit of 1KB.

TopicsDetectionJobFilter

Provides information for filtering topic detection jobs. For more information, see .

TopicsDetectionJobProperties

Provides information about a topic detection job.

ToxicContent

Toxic content analysis result for one string. For more information about toxicity detection, see Toxicity detection in the Amazon Comprehend Developer Guide

ToxicLabels

Toxicity analysis result for one string. For more information about toxicity detection, see Toxicity detection in the Amazon Comprehend Developer Guide.

UpdateDataSecurityConfig

Data security configuration.

VpcConfig

Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for the job. For more information, see Amazon VPC.

WarningsListItem

The system identified one of the following warnings while processing the input document:

• The document to classify is plain text, but the classifier is a native document model.

• The document to classify is semi-structured, but the classifier is a plain-text model.

Enums

AugmentedManifestsDocumentTypeFormat

When writing a match expression against AugmentedManifestsDocumentTypeFormat, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

BlockType

When writing a match expression against BlockType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

DatasetDataFormat

When writing a match expression against DatasetDataFormat, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

DatasetStatus

When writing a match expression against DatasetStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

DatasetType

When writing a match expression against DatasetType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

DocumentClassifierDataFormat

When writing a match expression against DocumentClassifierDataFormat, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

DocumentClassifierDocumentTypeFormat

When writing a match expression against DocumentClassifierDocumentTypeFormat, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

DocumentClassifierMode

When writing a match expression against DocumentClassifierMode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

DocumentReadAction

When writing a match expression against DocumentReadAction, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

DocumentReadFeatureTypes

When writing a match expression against DocumentReadFeatureTypes, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

DocumentReadMode

When writing a match expression against DocumentReadMode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

DocumentType

When writing a match expression against DocumentType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

EndpointStatus

When writing a match expression against EndpointStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

EntityRecognizerDataFormat

When writing a match expression against EntityRecognizerDataFormat, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

EntityType

When writing a match expression against EntityType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

FlywheelIterationStatus

When writing a match expression against FlywheelIterationStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

FlywheelStatus

When writing a match expression against FlywheelStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

InputFormat

When writing a match expression against InputFormat, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

InvalidRequestDetailReason

When writing a match expression against InvalidRequestDetailReason, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

InvalidRequestReason

When writing a match expression against InvalidRequestReason, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

JobStatus

When writing a match expression against JobStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

LanguageCode

When writing a match expression against LanguageCode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

ModelStatus

When writing a match expression against ModelStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

ModelType

When writing a match expression against ModelType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

PageBasedErrorCode

When writing a match expression against PageBasedErrorCode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

PageBasedWarningCode

When writing a match expression against PageBasedWarningCode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

PartOfSpeechTagType

When writing a match expression against PartOfSpeechTagType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

PiiEntitiesDetectionMaskMode

When writing a match expression against PiiEntitiesDetectionMaskMode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

PiiEntitiesDetectionMode

When writing a match expression against PiiEntitiesDetectionMode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

PiiEntityType

When writing a match expression against PiiEntityType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

RelationshipType

When writing a match expression against RelationshipType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

SentimentType

When writing a match expression against SentimentType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

Split

When writing a match expression against Split, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

SyntaxLanguageCode

When writing a match expression against SyntaxLanguageCode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

TargetedSentimentEntityType

When writing a match expression against TargetedSentimentEntityType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.

ToxicContentType

When writing a match expression against ToxicContentType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.