Module Awso_comprehend_asyncSource

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

Nested block contained within a block.

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.

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

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.

A reference to a block.

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

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.

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

The X and Y coordinates of a point on a document page. For additional information, see Point in the Amazon Textract API reference.

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.

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.

Describes the annotations associated with a entity recognizer.

Describes the training documents submitted with an entity recognizer.

Describes the entity list submitted with an entity recognizer.

Detailed information about the accuracy of an entity recognizer.

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

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

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

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.

List of child blocks for the current block.

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.

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.

Describes a key noun phrase.

Provides information about an entity.

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.

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.

Configuration required for a document classification model.

Configuration required for an entity recognition model.

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

Provides configuration parameters for the output of inference jobs.

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

Provides configuration parameters for PII entity redaction.

The evaluation metrics associated with the evaluated model.

Specifies the format and location of the input data.

Detailed information about an entity recognizer.

Output data configuration.

Provides information about a document classifier.

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.

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

Array of the number of characters extracted from each page.

Information about the location of items on a document page. For additional information, see Geometry in the Amazon Textract API reference.

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.

Describes the annotations associated with a entity recognizer.

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

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.

Data security configuration.

Configuration about the model associated with a flywheel.

Provides additional detail about why the request failed.

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.

Provides information about a topic detection job.

Provides information about a targeted sentiment detection job.

Provides information about a sentiment detection job.

Provides information about a PII entities detection job.

Provides information about a key phrases detection job.

Flywheel summary information.

The configuration properties of a flywheel iteration.

Provides information about an events detection job.

Describes information about an entity recognizer.

Describes the information about an entity recognizer and its versions.

Provides information about an entities detection job.

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

Provides information about a dominant language detection job.

Provides information about a document classifier.

Describes information about a document classifier and its versions.

Provides information about a document classification job.

Properties associated with the dataset.

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

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

Provides information about a PII entity.

Information about each word or line of text in the input document. For additional information, see Block in the Amazon Textract API reference.

Document type for each page in the document.

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.

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.

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

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

Specifies the class that categorizes the document being analyzed

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

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.

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.

Analysis results for one of the documents in the batch.

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

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

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

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

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

The flywheel properties.

An internal server error occurred. Retry your request.

The request is invalid.

The KMS customer managed key (CMK) entered cannot be validated. Verify the key and re-enter it.

The specified resource ARN was not found. Check the ARN and try your request again.

The number of requests exceeds the limit. Resubmit your request later.

Data security configuration.

The specified resource name is already in use. Use a different name and try your request again.

The maximum number of resources per account has been exceeded. Review the resources, and then try your request again.

The specified resource is not available. Check the resource and try your request again.

Concurrent modification of the tags associated with an Amazon Comprehend resource is not supported.

The request contains more tag keys than can be associated with a resource (50 tag keys per resource).

The request contains more tags than can be associated with a resource (50 tags per resource). The maximum number of tags includes both existing tags and those included in your current request.

The specified job was not found. Check the job ID and try again.

The filter specified for the operation is invalid. Specify a different filter.

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

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

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

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

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

Filter the flywheels based on creation time or flywheel status.

Filter the flywheel iterations based on creation time.

Provides information for filtering a list of event detection jobs.

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./>

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

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.

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

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.

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.

Filter the datasets based on creation time or dataset status.

The size of the input text exceeds the limit. Use a smaller document.

Amazon Comprehend can't process the language of the input text. For a list of supported languages, Supported languages in the Comprehend Developer Guide.

Information about the document, discovered during text extraction.

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

The number of documents in the request exceeds the limit of 25. Try your request again with fewer documents.

Update the configuration information for an existing flywheel.

Update the configuration information for an existing flywheel.

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

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

Removes a specific tag associated with an Amazon Comprehend resource.

Removes a specific tag associated with an Amazon Comprehend resource.

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.

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.

Stops an entity recognizer training job while in progress. If the training job state is TRAINING, the job is marked for termination and put into the STOP_REQUESTED state. If the training job completes before it can be stopped, it is put into the TRAINED; otherwise the training job is stopped and putted into the STOPPED state and the service sends back an HTTP 200 response with an empty HTTP body.

Stops an entity recognizer training job while in progress. If the training job state is TRAINING, the job is marked for termination and put into the STOP_REQUESTED state. If the training job completes before it can be stopped, it is put into the TRAINED; otherwise the training job is stopped and putted into the STOPPED state and the service sends back an HTTP 200 response with an empty HTTP body.

Stops a document classifier training job while in progress. If the training job state is TRAINING, the job is marked for termination and put into the STOP_REQUESTED state. If the training job completes before it can be stopped, it is put into the TRAINED; otherwise the training job is stopped and put into the STOPPED state and the service sends back an HTTP 200 response with an empty HTTP body.

Stops a document classifier training job while in progress. If the training job state is TRAINING, the job is marked for termination and put into the STOP_REQUESTED state. If the training job completes before it can be stopped, it is put into the TRAINED; otherwise the training job is stopped and put into the STOPPED state and the service sends back an HTTP 200 response with an empty HTTP body.

Stops a targeted sentiment detection job in progress. If the job state is IN_PROGRESS, the job is marked for termination and put into the STOP_REQUESTED state. If the job completes before it can be stopped, it is put into the COMPLETED state; otherwise the job is be stopped and put into the STOPPED state. If the job is in the COMPLETED or FAILED state when you call the StopDominantLanguageDetectionJob operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location.

Stops a targeted sentiment detection job in progress. If the job state is IN_PROGRESS, the job is marked for termination and put into the STOP_REQUESTED state. If the job completes before it can be stopped, it is put into the COMPLETED state; otherwise the job is be stopped and put into the STOPPED state. If the job is in the COMPLETED or FAILED state when you call the StopDominantLanguageDetectionJob operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location.

Stops a sentiment detection job in progress. If the job state is IN_PROGRESS, the job is marked for termination and put into the STOP_REQUESTED state. If the job completes before it can be stopped, it is put into the COMPLETED state; otherwise the job is be stopped and put into the STOPPED state. If the job is in the COMPLETED or FAILED state when you call the StopDominantLanguageDetectionJob operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location.

Stops a sentiment detection job in progress. If the job state is IN_PROGRESS, the job is marked for termination and put into the STOP_REQUESTED state. If the job completes before it can be stopped, it is put into the COMPLETED state; otherwise the job is be stopped and put into the STOPPED state. If the job is in the COMPLETED or FAILED state when you call the StopDominantLanguageDetectionJob operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location.

Stops a PII entities detection job in progress.

Stops a PII entities detection job in progress.

Stops a key phrases detection job in progress. If the job state is IN_PROGRESS the job is marked for termination and put into the STOP_REQUESTED state. If the job completes before it can be stopped, it is put into the COMPLETED state; otherwise the job is stopped and put into the STOPPED state. If the job is in the COMPLETED or FAILED state when you call the StopDominantLanguageDetectionJob operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location.

Stops a key phrases detection job in progress. If the job state is IN_PROGRESS the job is marked for termination and put into the STOP_REQUESTED state. If the job completes before it can be stopped, it is put into the COMPLETED state; otherwise the job is stopped and put into the STOPPED state. If the job is in the COMPLETED or FAILED state when you call the StopDominantLanguageDetectionJob operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location.

Stops an events detection job in progress.

Stops an events detection job in progress.

Stops an entities detection job in progress. If the job state is IN_PROGRESS the job is marked for termination and put into the STOP_REQUESTED state. If the job completes before it can be stopped, it is put into the COMPLETED state; otherwise the job is stopped and put into the STOPPED state. If the job is in the COMPLETED or FAILED state when you call the StopDominantLanguageDetectionJob operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location.

Stops an entities detection job in progress. If the job state is IN_PROGRESS the job is marked for termination and put into the STOP_REQUESTED state. If the job completes before it can be stopped, it is put into the COMPLETED state; otherwise the job is stopped and put into the STOPPED state. If the job is in the COMPLETED or FAILED state when you call the StopDominantLanguageDetectionJob operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location.

Stops a dominant language detection job in progress. If the job state is IN_PROGRESS the job is marked for termination and put into the STOP_REQUESTED state. If the job completes before it can be stopped, it is put into the COMPLETED state; otherwise the job is stopped and put into the STOPPED state. If the job is in the COMPLETED or FAILED state when you call the StopDominantLanguageDetectionJob operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location.

Stops a dominant language detection job in progress. If the job state is IN_PROGRESS the job is marked for termination and put into the STOP_REQUESTED state. If the job completes before it can be stopped, it is put into the COMPLETED state; otherwise the job is stopped and put into the STOPPED state. If the job is in the COMPLETED or FAILED state when you call the StopDominantLanguageDetectionJob operation, the operation returns a 400 Internal Request Exception. When a job is stopped, any documents already processed are written to the output location.

Starts an asynchronous topic detection job. Use the DescribeTopicDetectionJob operation to track the status of a job.

Starts an asynchronous topic detection job. Use the DescribeTopicDetectionJob operation to track the status of a job.

Starts an asynchronous targeted sentiment detection job for a collection of documents. Use the DescribeTargetedSentimentDetectionJob operation to track the status of a job.

Starts an asynchronous targeted sentiment detection job for a collection of documents. Use the DescribeTargetedSentimentDetectionJob operation to track the status of a job.

Starts an asynchronous sentiment detection job for a collection of documents. Use the operation to track the status of a job.

Starts an asynchronous sentiment detection job for a collection of documents. Use the operation to track the status of a job.

Starts an asynchronous PII entity detection job for a collection of documents.

Starts an asynchronous PII entity detection job for a collection of documents.

Starts an asynchronous key phrase detection job for a collection of documents. Use the operation to track the status of a job.

Starts an asynchronous key phrase detection job for a collection of documents. Use the operation to track the status of a job.

Start the flywheel iteration.This operation uses any new datasets to train a new model version. For more information about flywheels, see Flywheel overview in the Amazon Comprehend Developer Guide.

Start the flywheel iteration.This operation uses any new datasets to train a new model version. For more information about flywheels, see Flywheel overview in the Amazon Comprehend Developer Guide.

Starts an asynchronous event detection job for a collection of documents.

Starts an asynchronous event detection job for a collection of documents.

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 EntityRecognizerArn must be used in order to provide access to the recognizer being used to detect the custom entity.

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 EntityRecognizerArn must be used in order to provide access to the recognizer being used to detect the custom entity.

Starts an asynchronous dominant language detection job for a collection of documents. Use the operation to track the status of a job.

Starts an asynchronous dominant language detection job for a collection of documents. Use the operation to track the status of a job.

Starts an asynchronous document classification job using a custom classification model. Use the DescribeDocumentClassificationJob operation to track the progress of the job.

Starts an asynchronous document classification job using a custom classification model. Use the DescribeDocumentClassificationJob operation to track the progress of the job.

Attaches a resource-based policy to a custom model. You can use this policy to authorize an entity in another Amazon Web Services account to import the custom model, which replicates it in Amazon Comprehend in their account.

Attaches a resource-based policy to a custom model. You can use this policy to authorize an entity in another Amazon Web Services account to import the custom model, which replicates it in Amazon Comprehend in their account.

Gets a list of the topic detection jobs that you have submitted.

Gets a list of the topic detection jobs that you have submitted.

Gets a list of targeted sentiment detection jobs that you have submitted.

Gets a list of targeted sentiment detection jobs that you have submitted.

Lists all tags associated with a given Amazon Comprehend resource.

Lists all tags associated with a given Amazon Comprehend resource.

Gets a list of sentiment detection jobs that you have submitted.

Gets a list of sentiment detection jobs that you have submitted.

Gets a list of the PII entity detection jobs that you have submitted.

Gets a list of the PII entity detection jobs that you have submitted.

Get a list of key phrase detection jobs that you have submitted.

Get a list of key phrase detection jobs that you have submitted.

Gets a list of the flywheels that you have created.

Gets a list of the flywheels that you have created.

Information about the history of a flywheel iteration. For more information about flywheels, see Flywheel overview in the Amazon Comprehend Developer Guide.

Information about the history of a flywheel iteration. For more information about flywheels, see Flywheel overview in the Amazon Comprehend Developer Guide.

Gets a list of the events detection jobs that you have submitted.

Gets a list of the events detection jobs that you have submitted.

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.

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.

Gets a list of summaries for the entity recognizers that you have created.

Gets a list of summaries for the entity recognizers that you have created.

Gets a list of the entity detection jobs that you have submitted.

Gets a list of the entity detection jobs that you have submitted.

Gets a list of all existing endpoints that you've created. For information about endpoints, see Managing endpoints.

Gets a list of all existing endpoints that you've created. For information about endpoints, see Managing endpoints.

Gets a list of the dominant language detection jobs that you have submitted.

Gets a list of the dominant language detection jobs that you have submitted.

Gets a list of the document classifiers that you have created.

Gets a list of the document classifiers that you have created.

Gets a list of summaries of the document classifiers that you have created

Gets a list of summaries of the document classifiers that you have created

Gets a list of the documentation classification jobs that you have submitted.

Gets a list of the documentation classification jobs that you have submitted.

List the datasets that you have configured in this Region. For more information about datasets, see Flywheel overview in the Amazon Comprehend Developer Guide.

List the datasets that you have configured in this Region. For more information about datasets, see Flywheel overview in the Amazon Comprehend Developer Guide.

Creates a new custom model that replicates a source custom model that you import. The source model can be in your Amazon Web Services account or another one. If the source model is in another Amazon Web Services account, then it must have a resource-based policy that authorizes you to import it. The source model must be in the same Amazon Web Services Region that you're using when you import. You can't import a model that's in a different Region.

Creates a new custom model that replicates a source custom model that you import. The source model can be in your Amazon Web Services account or another one. If the source model is in another Amazon Web Services account, then it must have a resource-based policy that authorizes you to import it. The source model must be in the same Amazon Web Services Region that you're using when you import. You can't import a model that's in a different Region.

Performs toxicity analysis on the list of text strings that you provide as input. The API response contains a results list that matches the size of the input list. For more information about toxicity detection, see Toxicity detection in the Amazon Comprehend Developer Guide.

Performs toxicity analysis on the list of text strings that you provide as input. The API response contains a results list that matches the size of the input list. For more information about toxicity detection, see Toxicity detection in the Amazon Comprehend Developer Guide.

Inspects the input text and returns a sentiment analysis for each entity identified in the text. For more information about targeted sentiment, see Targeted sentiment in the Amazon Comprehend Developer Guide.

Inspects the input text and returns a sentiment analysis for each entity identified in the text. For more information about targeted sentiment, see Targeted sentiment in the Amazon Comprehend Developer Guide.

Inspects text for syntax and the part of speech of words in the document. For more information, see Syntax in the Comprehend Developer Guide.

Inspects text for syntax and the part of speech of words in the document. For more information, see Syntax in the Comprehend Developer Guide.

Inspects text and returns an inference of the prevailing sentiment (POSITIVE, NEUTRAL, MIXED, or NEGATIVE).

Inspects text and returns an inference of the prevailing sentiment (POSITIVE, NEUTRAL, MIXED, or NEGATIVE).

Inspects the input text for entities that contain personally identifiable information (PII) and returns information about them.

Inspects the input text for entities that contain personally identifiable information (PII) and returns information about them.

Detects the key noun phrases found in the text.

Detects the key noun phrases found in the text.

Detects named entities in input text when you use the pre-trained model. Detects custom entities if you have a custom entity recognition model. When detecting named entities using the pre-trained model, use plain text as the input. For more information about named entities, see Entities in the Comprehend Developer Guide. When you use a custom entity recognition model, you can input plain text or you can upload a single-page input document (text, PDF, Word, or image). If the system detects errors while processing a page in the input document, the API response includes an entry in Errors for each error. If the system detects a document-level error in your input document, the API returns an InvalidRequestException error response. For details about this exception, see Errors in semi-structured documents in the Comprehend Developer Guide.

Detects named entities in input text when you use the pre-trained model. Detects custom entities if you have a custom entity recognition model. When detecting named entities using the pre-trained model, use plain text as the input. For more information about named entities, see Entities in the Comprehend Developer Guide. When you use a custom entity recognition model, you can input plain text or you can upload a single-page input document (text, PDF, Word, or image). If the system detects errors while processing a page in the input document, the API response includes an entry in Errors for each error. If the system detects a document-level error in your input document, the API returns an InvalidRequestException error response. For details about this exception, see Errors in semi-structured documents in the Comprehend Developer Guide.

Determines the dominant language of the input text. For a list of languages that Amazon Comprehend can detect, see Amazon Comprehend Supported Languages.

Determines the dominant language of the input text. For a list of languages that Amazon Comprehend can detect, see Amazon Comprehend Supported Languages.

Gets the properties associated with a topic detection job. Use this operation to get the status of a detection job.

Gets the properties associated with a topic detection job. Use this operation to get the status of a detection job.

Gets the properties associated with a targeted sentiment detection job. Use this operation to get the status of the job.

Gets the properties associated with a targeted sentiment detection job. Use this operation to get the status of the job.

Gets the properties associated with a sentiment detection job. Use this operation to get the status of a detection job.

Gets the properties associated with a sentiment detection job. Use this operation to get the status of a detection job.

Gets the details of a resource-based policy that is attached to a custom model, including the JSON body of the policy.

Gets the details of a resource-based policy that is attached to a custom model, including the JSON body of the policy.

Gets the properties associated with a PII entities detection job. For example, you can use this operation to get the job status.

Gets the properties associated with a PII entities detection job. For example, you can use this operation to get the job status.

Gets the properties associated with a key phrases detection job. Use this operation to get the status of a detection job.

Gets the properties associated with a key phrases detection job. Use this operation to get the status of a detection job.

Provides configuration information about the flywheel. For more information about flywheels, see Flywheel overview in the Amazon Comprehend Developer Guide.

Provides configuration information about the flywheel. For more information about flywheels, see Flywheel overview in the Amazon Comprehend Developer Guide.

Retrieve the configuration properties of a flywheel iteration. For more information about flywheels, see Flywheel overview in the Amazon Comprehend Developer Guide.

Retrieve the configuration properties of a flywheel iteration. For more information about flywheels, see Flywheel overview in the Amazon Comprehend Developer Guide.

Gets the status and details of an events detection job.

Gets the status and details of an events detection job.

Provides details about an entity recognizer including status, S3 buckets containing training data, recognizer metadata, metrics, and so on.

Provides details about an entity recognizer including status, S3 buckets containing training data, recognizer metadata, metrics, and so on.

Gets the properties associated with an entities detection job. Use this operation to get the status of a detection job.

Gets the properties associated with an entities detection job. Use this operation to get the status of a detection job.

Gets the properties associated with a specific endpoint. Use this operation to get the status of an endpoint. For information about endpoints, see Managing endpoints.

Gets the properties associated with a specific endpoint. Use this operation to get the status of an endpoint. For information about endpoints, see Managing endpoints.

Gets the properties associated with a dominant language detection job. Use this operation to get the status of a detection job.

Gets the properties associated with a dominant language detection job. Use this operation to get the status of a detection job.

Gets the properties associated with a document classifier.

Gets the properties associated with a document classifier.

Gets the properties associated with a document classification job. Use this operation to get the status of a classification job.

Gets the properties associated with a document classification job. Use this operation to get the status of a classification job.

Returns information about the dataset that you specify. For more information about datasets, see Flywheel overview in the Amazon Comprehend Developer Guide.

Returns information about the dataset that you specify. For more information about datasets, see Flywheel overview in the Amazon Comprehend Developer Guide.

Deletes a resource-based policy that is attached to a custom model.

Deletes a resource-based policy that is attached to a custom model.

Deletes a flywheel. When you delete the flywheel, Amazon Comprehend does not delete the data lake or the model associated with the flywheel. For more information about flywheels, see Flywheel overview in the Amazon Comprehend Developer Guide.

Deletes a flywheel. When you delete the flywheel, Amazon Comprehend does not delete the data lake or the model associated with the flywheel. For more information about flywheels, see Flywheel overview in the Amazon Comprehend Developer Guide.

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 ResourceInUseException 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.

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 ResourceInUseException 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.

Deletes a model-specific endpoint for a previously-trained custom model. All endpoints must be deleted in order for the model to be deleted. For information about endpoints, see Managing endpoints.

Deletes a model-specific endpoint for a previously-trained custom model. All endpoints must be deleted in order for the model to be deleted. For information about endpoints, see Managing endpoints.

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 ResourceInUseException 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.

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 ResourceInUseException 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.

A flywheel is an Amazon Web Services resource that orchestrates the ongoing training of a model for custom classification or custom entity recognition. You can create a flywheel to start with an existing trained model, or Comprehend can create and train a new model. When you create the flywheel, Comprehend creates a data lake in your account. The data lake holds the training data and test data for all versions of the model. To use a flywheel with an existing trained model, you specify the active model version. Comprehend copies the model's training data and test data into the flywheel's data lake. To use the flywheel with a new model, you need to provide a dataset for training data (and optional test data) when you create the flywheel. For more information about flywheels, see Flywheel overview in the Amazon Comprehend Developer Guide.

A flywheel is an Amazon Web Services resource that orchestrates the ongoing training of a model for custom classification or custom entity recognition. You can create a flywheel to start with an existing trained model, or Comprehend can create and train a new model. When you create the flywheel, Comprehend creates a data lake in your account. The data lake holds the training data and test data for all versions of the model. To use a flywheel with an existing trained model, you specify the active model version. Comprehend copies the model's training data and test data into the flywheel's data lake. To use the flywheel with a new model, you need to provide a dataset for training data (and optional test data) when you create the flywheel. For more information about flywheels, see Flywheel overview in the Amazon Comprehend Developer Guide.

Creates an entity recognizer using submitted files. After your CreateEntityRecognizer request is submitted, you can check job status using the DescribeEntityRecognizer API.

Creates an entity recognizer using submitted files. After your CreateEntityRecognizer request is submitted, you can check job status using the DescribeEntityRecognizer API.

Creates a model-specific endpoint for synchronous inference for a previously trained custom model For information about endpoints, see Managing endpoints.

Creates a model-specific endpoint for synchronous inference for a previously trained custom model For information about endpoints, see Managing endpoints.

Creates a new document classifier that you can use to categorize documents. To create a classifier, you provide a set of training documents that are labeled with the categories that you want to use. For more information, see Training classifier models in the Comprehend Developer Guide.

Creates a new document classifier that you can use to categorize documents. To create a classifier, you provide a set of training documents that are labeled with the categories that you want to use. For more information, see Training classifier models in the Comprehend Developer Guide.

Creates a dataset to upload training or test data for a model associated with a flywheel. For more information about datasets, see Flywheel overview in the Amazon Comprehend Developer Guide.

Creates a dataset to upload training or test data for a model associated with a flywheel. For more information about datasets, see Flywheel overview in the Amazon Comprehend Developer Guide.

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.

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.

Creates a classification request to analyze a single document in real-time. ClassifyDocument supports the following model types: Custom classifier - a custom model that you have created and trained. For input, you can provide plain text, a single-page document (PDF, Word, or image), or Amazon Textract API output. For more information, see Custom classification in the Amazon Comprehend Developer Guide. Prompt safety classifier - Amazon Comprehend provides a pre-trained model for classifying input prompts for generative AI applications. For input, you provide English plain text input. For prompt safety classification, the response includes only the Classes field. For more information about prompt safety classifiers, see Prompt safety classification in the Amazon Comprehend Developer Guide. If the system detects errors while processing a page in the input document, the API response includes an Errors field that describes the errors. If the system detects a document-level error in your input document, the API returns an InvalidRequestException error response. For details about this exception, see Errors in semi-structured documents in the Comprehend Developer Guide.

Creates a classification request to analyze a single document in real-time. ClassifyDocument supports the following model types: Custom classifier - a custom model that you have created and trained. For input, you can provide plain text, a single-page document (PDF, Word, or image), or Amazon Textract API output. For more information, see Custom classification in the Amazon Comprehend Developer Guide. Prompt safety classifier - Amazon Comprehend provides a pre-trained model for classifying input prompts for generative AI applications. For input, you provide English plain text input. For prompt safety classification, the response includes only the Classes field. For more information about prompt safety classifiers, see Prompt safety classification in the Amazon Comprehend Developer Guide. If the system detects errors while processing a page in the input document, the API response includes an Errors field that describes the errors. If the system detects a document-level error in your input document, the API returns an InvalidRequestException error response. For details about this exception, see Errors in semi-structured documents in the Comprehend Developer Guide.

Inspects a batch of documents and returns a sentiment analysis for each entity identified in the documents. For more information about targeted sentiment, see Targeted sentiment in the Amazon Comprehend Developer Guide.

Inspects a batch of documents and returns a sentiment analysis for each entity identified in the documents. For more information about targeted sentiment, see Targeted sentiment in the Amazon Comprehend Developer Guide.

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 Syntax in the Comprehend Developer Guide.

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 Syntax in the Comprehend Developer Guide.

Inspects a batch of documents and returns an inference of the prevailing sentiment, POSITIVE, NEUTRAL, MIXED, or NEGATIVE, in each one.

Inspects a batch of documents and returns an inference of the prevailing sentiment, POSITIVE, NEUTRAL, MIXED, or NEGATIVE, in each one.

Detects the key noun phrases found in a batch of documents.

Detects the key noun phrases found in a batch of documents.

Inspects the text of a batch of documents for named entities and returns information about them. For more information about named entities, see Entities in the Comprehend Developer Guide.

Inspects the text of a batch of documents for named entities and returns information about them. For more information about named entities, see Entities in the Comprehend Developer Guide.

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.

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.