AWS Comprehend (version v1.*.*)

batch_detect_dominant_language#

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.

{
  "TextList" : [ "string" ]
}

batch_detect_entities#

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

{
  "LanguageCode" : "The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend: German (\"de\"), English (\"en\"), Spanish (\"es\"), French (\"fr\"), Italian (\"it\"), or Portuguese (\"pt\"). All documents must be in the same language.",
  "TextList" : [ "string" ]
}

batch_detect_key_phrases#

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

{
  "LanguageCode" : "The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend: German (\"de\"), English (\"en\"), Spanish (\"es\"), French (\"fr\"), Italian (\"it\"), or Portuguese (\"pt\"). All documents must be in the same language.",
  "TextList" : [ "string" ]
}

batch_detect_sentiment#

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

{
  "LanguageCode" : "The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend: German (\"de\"), English (\"en\"), Spanish (\"es\"), French (\"fr\"), Italian (\"it\"), or Portuguese (\"pt\"). All documents must be in the same language.",
  "TextList" : [ "string" ]
}

batch_detect_syntax#

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.

{
  "LanguageCode" : "The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend: German (\"de\"), English (\"en\"), Spanish (\"es\"), French (\"fr\"), Italian (\"it\"), or Portuguese (\"pt\"). All documents must be in the same language.",
  "TextList" : [ "string" ]
}

create_document_classifier#

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.

{
  "ClientRequestToken" : "A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.",
  "LanguageCode" : "The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend: German (\"de\"), English (\"en\"), Spanish (\"es\"), French (\"fr\"), Italian (\"it\"), or Portuguese (\"pt\"). All documents must be in the same language.",
  "DataAccessRoleArn" : "The Amazon Resource Name (ARN) of the AWS Identity and Management (IAM) role that grants Amazon Comprehend read access to your input data.",
  "OutputDataConfig" : {
    "KmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"   \n KMS Key Alias: \"alias/ExampleAlias\"   \n ARN of a KMS Key Alias: \"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"  ",
    "S3Uri" : "When you use the OutputDataConfig object while creating a custom classifier, you specify the Amazon S3 location where you want to write the confusion matrix. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of this output file. \nWhen the custom classifier job is finished, the service creates the output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz. It is a compressed archive that contains the confusion matrix."
  },
  "VpcConfig" : {
    "Subnets" : [ "string" ],
    "SecurityGroupIds" : [ "string" ]
  },
  "DocumentClassifierName" : "The name of the document classifier.",
  "VolumeKmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"  ",
  "InputDataConfig" : {
    "S3Uri" : "The Amazon S3 URI for the input data. The S3 bucket must be in the same region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of input files. \nFor example, if you use the URI S3://bucketName/prefix, if the prefix is a single file, Amazon Comprehend uses that file as input. If more than one file begins with the prefix, Amazon Comprehend uses all of them as input."
  },
  "Tags" : [ {
    "Value" : " The second part of a key-value pair that forms a tag associated with a given resource. For instance, if you want to show which resources are used by which departments, you might use “Department” as the initial (key) portion of the pair, with a value of “sales” to indicate the sales department. ",
    "Key" : "The initial part of a key-value pair that forms a tag associated with a given resource. For instance, if you want to show which resources are used by which departments, you might use “Department” as the key portion of the pair, with multiple possible values such as “sales,” “legal,” and “administration.” "
  } ]
}

create_entity_recognizer#

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

{
  "ClientRequestToken" : " A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.",
  "LanguageCode" : " The language of the input documents. All documents must be in the same language. Only English (\"en\") is currently supported. ",
  "DataAccessRoleArn" : "The Amazon Resource Name (ARN) of the AWS Identity and Management (IAM) role that grants Amazon Comprehend read access to your input data.",
  "VpcConfig" : {
    "Subnets" : [ "string" ],
    "SecurityGroupIds" : [ "string" ]
  },
  "VolumeKmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"  ",
  "RecognizerName" : "The name given to the newly created recognizer. Recognizer names can be a maximum of 256 characters. Alphanumeric characters, hyphens (-) and underscores (_) are allowed. The name must be unique in the account/region.",
  "InputDataConfig" : {
    "EntityTypes" : [ {
      "Type" : "Entity type of an item on an entity type list."
    } ],
    "Annotations" : {
      "S3Uri" : " Specifies the Amazon S3 location where the annotations for an entity recognizer are located. The URI must be in the same region as the API endpoint that you are calling."
    },
    "Documents" : {
      "S3Uri" : " Specifies the Amazon S3 location where the training documents for an entity recognizer are located. The URI must be in the same region as the API endpoint that you are calling."
    },
    "EntityList" : {
      "S3Uri" : "Specifies the Amazon S3 location where the entity list is located. The URI must be in the same region as the API endpoint that you are calling."
    }
  },
  "Tags" : [ {
    "Value" : " The second part of a key-value pair that forms a tag associated with a given resource. For instance, if you want to show which resources are used by which departments, you might use “Department” as the initial (key) portion of the pair, with a value of “sales” to indicate the sales department. ",
    "Key" : "The initial part of a key-value pair that forms a tag associated with a given resource. For instance, if you want to show which resources are used by which departments, you might use “Department” as the key portion of the pair, with multiple possible values such as “sales,” “legal,” and “administration.” "
  } ]
}

delete_document_classifier#

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.

{
  "DocumentClassifierArn" : "The Amazon Resource Name (ARN) that identifies the document classifier. "
}

delete_entity_recognizer#

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.

{
  "EntityRecognizerArn" : "The Amazon Resource Name (ARN) that identifies the entity recognizer."
}

describe_document_classification_job#

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

{
  "JobId" : "The identifier that Amazon Comprehend generated for the job. The operation returns this identifier in its response."
}

describe_document_classifier#

Gets the properties associated with a document classifier.

{
  "DocumentClassifierArn" : "The Amazon Resource Name (ARN) that identifies the document classifier. The operation returns this identifier in its response."
}

describe_dominant_language_detection_job#

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

{
  "JobId" : "The identifier that Amazon Comprehend generated for the job. The operation returns this identifier in its response."
}

describe_entities_detection_job#

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

{
  "JobId" : "The identifier that Amazon Comprehend generated for the job. The operation returns this identifier in its response."
}

describe_entity_recognizer#

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

{
  "EntityRecognizerArn" : "The Amazon Resource Name (ARN) that identifies the entity recognizer."
}

describe_key_phrases_detection_job#

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

{
  "JobId" : "The identifier that Amazon Comprehend generated for the job. The operation returns this identifier in its response."
}

describe_sentiment_detection_job#

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

{
  "JobId" : "The identifier that Amazon Comprehend generated for the job. The operation returns this identifier in its response."
}

describe_topics_detection_job#

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

{
  "JobId" : "The identifier assigned by the user to the detection job."
}

detect_dominant_language#

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

{
  "Text" : "A UTF-8 text string. Each string should contain at least 20 characters and must contain fewer that 5,000 bytes of UTF-8 encoded characters."
}

detect_entities#

Inspects text for named entities, and returns information about them. For more information, about named entities, see how-entities.

{
  "LanguageCode" : "The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend: German (\"de\"), English (\"en\"), Spanish (\"es\"), French (\"fr\"), Italian (\"it\"), or Portuguese (\"pt\"). All documents must be in the same language.",
  "Text" : "A UTF-8 text string. Each string must contain fewer that 5,000 bytes of UTF-8 encoded characters."
}

detect_key_phrases#

Detects the key noun phrases found in the text.

{
  "LanguageCode" : "The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend: German (\"de\"), English (\"en\"), Spanish (\"es\"), French (\"fr\"), Italian (\"it\"), or Portuguese (\"pt\"). All documents must be in the same language.",
  "Text" : "A UTF-8 text string. Each string must contain fewer that 5,000 bytes of UTF-8 encoded characters."
}

detect_sentiment#

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

{
  "LanguageCode" : "The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend: German (\"de\"), English (\"en\"), Spanish (\"es\"), French (\"fr\"), Italian (\"it\"), or Portuguese (\"pt\"). All documents must be in the same language.",
  "Text" : "A UTF-8 text string. Each string must contain fewer that 5,000 bytes of UTF-8 encoded characters."
}

detect_syntax#

Inspects text for syntax and the part of speech of words in the document. For more information, how-syntax.

{
  "LanguageCode" : "The language code of the input documents. You can specify any of the primary languages supported by Amazon Comprehend: German (\"de\"), English (\"en\"), Spanish (\"es\"), French (\"fr\"), Italian (\"it\"), or Portuguese (\"pt\").",
  "Text" : "A UTF-8 string. Each string must contain fewer that 5,000 bytes of UTF encoded characters."
}

list_document_classification_jobs#

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

{
  "Filter" : {
    "JobStatus" : "Filters the list based on job status. Returns only jobs with the specified status.",
    "SubmitTimeAfter" : "Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted before the specified time. Jobs are returned in descending order, newest to oldest.",
    "SubmitTimeBefore" : "Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted after the specified time. Jobs are returned in ascending order, oldest to newest.",
    "JobName" : "Filters on the name of the job."
  }
}

list_document_classifiers#

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

{
  "Filter" : {
    "Status" : "Filters the list of classifiers based on status. ",
    "SubmitTimeAfter" : "Filters the list of classifiers based on the time that the classifier was submitted for processing. Returns only classifiers submitted after the specified time. Classifiers are returned in descending order, newest to oldest.",
    "SubmitTimeBefore" : "Filters the list of classifiers based on the time that the classifier was submitted for processing. Returns only classifiers submitted before the specified time. Classifiers are returned in ascending order, oldest to newest."
  }
}

list_dominant_language_detection_jobs#

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

{
  "Filter" : {
    "JobStatus" : "Filters the list of jobs based on job status. Returns only jobs with the specified status.",
    "SubmitTimeAfter" : "Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted after the specified time. Jobs are returned in descending order, newest to oldest.",
    "SubmitTimeBefore" : "Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted before the specified time. Jobs are returned in ascending order, oldest to newest.",
    "JobName" : "Filters on the name of the job."
  }
}

list_entities_detection_jobs#

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

{
  "Filter" : {
    "JobStatus" : "Filters the list of jobs based on job status. Returns only jobs with the specified status.",
    "SubmitTimeAfter" : "Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted after the specified time. Jobs are returned in descending order, newest to oldest.",
    "SubmitTimeBefore" : "Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted before the specified time. Jobs are returned in ascending order, oldest to newest.",
    "JobName" : "Filters on the name of the job."
  }
}

list_entity_recognizers#

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.

{
  "Filter" : {
    "Status" : "The status of an entity recognizer.",
    "SubmitTimeAfter" : "Filters the list of entities based on the time that the list was submitted for processing. Returns only jobs submitted after the specified time. Jobs are returned in ascending order, oldest to newest.",
    "SubmitTimeBefore" : "Filters the list of entities based on the time that the list was submitted for processing. Returns only jobs submitted before the specified time. Jobs are returned in descending order, newest to oldest."
  }
}

list_key_phrases_detection_jobs#

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

{
  "Filter" : {
    "JobStatus" : "Filters the list of jobs based on job status. Returns only jobs with the specified status.",
    "SubmitTimeAfter" : "Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted after the specified time. Jobs are returned in descending order, newest to oldest.",
    "SubmitTimeBefore" : "Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted before the specified time. Jobs are returned in ascending order, oldest to newest.",
    "JobName" : "Filters on the name of the job."
  }
}

list_sentiment_detection_jobs#

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

{
  "Filter" : {
    "JobStatus" : "Filters the list of jobs based on job status. Returns only jobs with the specified status.",
    "SubmitTimeAfter" : "Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted after the specified time. Jobs are returned in descending order, newest to oldest.",
    "SubmitTimeBefore" : "Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted before the specified time. Jobs are returned in ascending order, oldest to newest.",
    "JobName" : "Filters on the name of the job."
  }
}

list_tags_for_resource#

Lists all tags associated with a given Amazon Comprehend resource.

{
  "ResourceArn" : "The Amazon Resource Name (ARN) of the given Amazon Comprehend resource you are querying. "
}

list_topics_detection_jobs#

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

{
  "Filter" : {
    "JobStatus" : "Filters the list of topic detection jobs based on job status. Returns only jobs with the specified status.",
    "SubmitTimeAfter" : "Filters the list of jobs based on the time that the job was submitted for processing. Only returns jobs submitted after the specified time. Jobs are returned in ascending order, oldest to newest.",
    "SubmitTimeBefore" : "Filters the list of jobs based on the time that the job was submitted for processing. Only returns jobs submitted before the specified time. Jobs are returned in descending order, newest to oldest.",
    "JobName" : "string"
  }
}

start_document_classification_job#

Starts an asynchronous document classification job. Use the operation to track the progress of the job.

{
  "ClientRequestToken" : "A unique identifier for the request. If you do not set the client request token, Amazon Comprehend generates one.",
  "DataAccessRoleArn" : "The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data.",
  "OutputDataConfig" : {
    "KmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"   \n KMS Key Alias: \"alias/ExampleAlias\"   \n ARN of a KMS Key Alias: \"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"  ",
    "S3Uri" : "When you use the OutputDataConfig object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output file. \nWhen the topic detection job is finished, the service creates an output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz. It is a compressed archive that contains the ouput of the operation."
  },
  "VpcConfig" : {
    "Subnets" : [ "string" ],
    "SecurityGroupIds" : [ "string" ]
  },
  "JobName" : "The identifier of the job.",
  "VolumeKmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"  ",
  "DocumentClassifierArn" : "The Amazon Resource Name (ARN) of the document classifier to use to process the job.",
  "InputDataConfig" : {
    "S3Uri" : "The Amazon S3 URI for the input data. The URI must be in same region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of data files.  \nFor example, if you use the URI S3://bucketName/prefix, if the prefix is a single file, Amazon Comprehend uses that file as input. If more than one file begins with the prefix, Amazon Comprehend uses all of them as input.",
    "InputFormat" : "Specifies how the text in an input file should be processed:  \n  ONE_DOC_PER_FILE - Each file is considered a separate document. Use this option when you are processing large documents, such as newspaper articles or scientific papers.  \n  ONE_DOC_PER_LINE - Each line in a file is considered a separate document. Use this option when you are processing many short documents, such as text messages. "
  }
}

start_dominant_language_detection_job#

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

{
  "ClientRequestToken" : "A unique identifier for the request. If you do not set the client request token, Amazon Comprehend generates one.",
  "DataAccessRoleArn" : "The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data. For more information, see https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.",
  "OutputDataConfig" : {
    "KmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"   \n KMS Key Alias: \"alias/ExampleAlias\"   \n ARN of a KMS Key Alias: \"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"  ",
    "S3Uri" : "When you use the OutputDataConfig object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output file. \nWhen the topic detection job is finished, the service creates an output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz. It is a compressed archive that contains the ouput of the operation."
  },
  "VpcConfig" : {
    "Subnets" : [ "string" ],
    "SecurityGroupIds" : [ "string" ]
  },
  "JobName" : "An identifier for the job.",
  "VolumeKmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"  ",
  "InputDataConfig" : {
    "S3Uri" : "The Amazon S3 URI for the input data. The URI must be in same region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of data files.  \nFor example, if you use the URI S3://bucketName/prefix, if the prefix is a single file, Amazon Comprehend uses that file as input. If more than one file begins with the prefix, Amazon Comprehend uses all of them as input.",
    "InputFormat" : "Specifies how the text in an input file should be processed:  \n  ONE_DOC_PER_FILE - Each file is considered a separate document. Use this option when you are processing large documents, such as newspaper articles or scientific papers.  \n  ONE_DOC_PER_LINE - Each line in a file is considered a separate document. Use this option when you are processing many short documents, such as text messages. "
  }
}

start_entities_detection_job#

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.

{
  "LanguageCode" : "The language of the input documents. All documents must be in the same language. You can specify any of the languages supported by Amazon Comprehend: English (\"en\"), Spanish (\"es\"), French (\"fr\"), German (\"de\"), Italian (\"it\"), or Portuguese (\"pt\"). If custom entities recognition is used, this parameter is ignored and the language used for training the model is used instead.",
  "ClientRequestToken" : "A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.",
  "DataAccessRoleArn" : "The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data. For more information, see https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.",
  "OutputDataConfig" : {
    "KmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"   \n KMS Key Alias: \"alias/ExampleAlias\"   \n ARN of a KMS Key Alias: \"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"  ",
    "S3Uri" : "When you use the OutputDataConfig object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output file. \nWhen the topic detection job is finished, the service creates an output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz. It is a compressed archive that contains the ouput of the operation."
  },
  "VpcConfig" : {
    "Subnets" : [ "string" ],
    "SecurityGroupIds" : [ "string" ]
  },
  "JobName" : "The identifier of the job.",
  "VolumeKmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"  ",
  "InputDataConfig" : {
    "S3Uri" : "The Amazon S3 URI for the input data. The URI must be in same region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of data files.  \nFor example, if you use the URI S3://bucketName/prefix, if the prefix is a single file, Amazon Comprehend uses that file as input. If more than one file begins with the prefix, Amazon Comprehend uses all of them as input.",
    "InputFormat" : "Specifies how the text in an input file should be processed:  \n  ONE_DOC_PER_FILE - Each file is considered a separate document. Use this option when you are processing large documents, such as newspaper articles or scientific papers.  \n  ONE_DOC_PER_LINE - Each line in a file is considered a separate document. Use this option when you are processing many short documents, such as text messages. "
  },
  "EntityRecognizerArn" : "The Amazon Resource Name (ARN) that identifies the specific entity recognizer to be used by the StartEntitiesDetectionJob. This ARN is optional and is only used for a custom entity recognition job."
}

start_key_phrases_detection_job#

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

{
  "LanguageCode" : "The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend: German (\"de\"), English (\"en\"), Spanish (\"es\"), French (\"fr\"), Italian (\"it\"), or Portuguese (\"pt\"). All documents must be in the same language.",
  "ClientRequestToken" : "A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.",
  "DataAccessRoleArn" : "The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data. For more information, see https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.",
  "OutputDataConfig" : {
    "KmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"   \n KMS Key Alias: \"alias/ExampleAlias\"   \n ARN of a KMS Key Alias: \"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"  ",
    "S3Uri" : "When you use the OutputDataConfig object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output file. \nWhen the topic detection job is finished, the service creates an output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz. It is a compressed archive that contains the ouput of the operation."
  },
  "VpcConfig" : {
    "Subnets" : [ "string" ],
    "SecurityGroupIds" : [ "string" ]
  },
  "JobName" : "The identifier of the job.",
  "VolumeKmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"  ",
  "InputDataConfig" : {
    "S3Uri" : "The Amazon S3 URI for the input data. The URI must be in same region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of data files.  \nFor example, if you use the URI S3://bucketName/prefix, if the prefix is a single file, Amazon Comprehend uses that file as input. If more than one file begins with the prefix, Amazon Comprehend uses all of them as input.",
    "InputFormat" : "Specifies how the text in an input file should be processed:  \n  ONE_DOC_PER_FILE - Each file is considered a separate document. Use this option when you are processing large documents, such as newspaper articles or scientific papers.  \n  ONE_DOC_PER_LINE - Each line in a file is considered a separate document. Use this option when you are processing many short documents, such as text messages. "
  }
}

start_sentiment_detection_job#

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

{
  "LanguageCode" : "The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend: German (\"de\"), English (\"en\"), Spanish (\"es\"), French (\"fr\"), Italian (\"it\"), or Portuguese (\"pt\"). All documents must be in the same language.",
  "ClientRequestToken" : "A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.",
  "DataAccessRoleArn" : "The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data. For more information, see https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.",
  "OutputDataConfig" : {
    "KmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"   \n KMS Key Alias: \"alias/ExampleAlias\"   \n ARN of a KMS Key Alias: \"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"  ",
    "S3Uri" : "When you use the OutputDataConfig object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output file. \nWhen the topic detection job is finished, the service creates an output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz. It is a compressed archive that contains the ouput of the operation."
  },
  "VpcConfig" : {
    "Subnets" : [ "string" ],
    "SecurityGroupIds" : [ "string" ]
  },
  "JobName" : "The identifier of the job.",
  "VolumeKmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"  ",
  "InputDataConfig" : {
    "S3Uri" : "The Amazon S3 URI for the input data. The URI must be in same region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of data files.  \nFor example, if you use the URI S3://bucketName/prefix, if the prefix is a single file, Amazon Comprehend uses that file as input. If more than one file begins with the prefix, Amazon Comprehend uses all of them as input.",
    "InputFormat" : "Specifies how the text in an input file should be processed:  \n  ONE_DOC_PER_FILE - Each file is considered a separate document. Use this option when you are processing large documents, such as newspaper articles or scientific papers.  \n  ONE_DOC_PER_LINE - Each line in a file is considered a separate document. Use this option when you are processing many short documents, such as text messages. "
  }
}

start_topics_detection_job#

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

{
  "ClientRequestToken" : "A unique identifier for the request. If you do not set the client request token, Amazon Comprehend generates one.",
  "DataAccessRoleArn" : "The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data. For more information, see https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.",
  "OutputDataConfig" : {
    "KmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"   \n KMS Key Alias: \"alias/ExampleAlias\"   \n ARN of a KMS Key Alias: \"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"  ",
    "S3Uri" : "When you use the OutputDataConfig object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output file. \nWhen the topic detection job is finished, the service creates an output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz. It is a compressed archive that contains the ouput of the operation."
  },
  "VpcConfig" : {
    "Subnets" : [ "string" ],
    "SecurityGroupIds" : [ "string" ]
  },
  "JobName" : "The identifier of the job.",
  "VolumeKmsKeyId" : "ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:  \n KMS Key ID: \"1234abcd-12ab-34cd-56ef-1234567890ab\"   \n Amazon Resource Name (ARN) of a KMS Key: \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"  ",
  "NumberOfTopics" : "The number of topics to detect.",
  "InputDataConfig" : {
    "S3Uri" : "The Amazon S3 URI for the input data. The URI must be in same region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of data files.  \nFor example, if you use the URI S3://bucketName/prefix, if the prefix is a single file, Amazon Comprehend uses that file as input. If more than one file begins with the prefix, Amazon Comprehend uses all of them as input.",
    "InputFormat" : "Specifies how the text in an input file should be processed:  \n  ONE_DOC_PER_FILE - Each file is considered a separate document. Use this option when you are processing large documents, such as newspaper articles or scientific papers.  \n  ONE_DOC_PER_LINE - Each line in a file is considered a separate document. Use this option when you are processing many short documents, such as text messages. "
  }
}

stop_dominant_language_detection_job#

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.

{
  "JobId" : "The identifier of the dominant language detection job to stop."
}

stop_entities_detection_job#

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.

{
  "JobId" : "The identifier of the entities detection job to stop."
}

stop_key_phrases_detection_job#

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.

{
  "JobId" : "The identifier of the key phrases detection job to stop."
}

stop_sentiment_detection_job#

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.

{
  "JobId" : "The identifier of the sentiment detection job to stop."
}

stop_training_document_classifier#

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.

{
  "DocumentClassifierArn" : "The Amazon Resource Name (ARN) that identifies the document classifier currently being trained."
}

stop_training_entity_recognizer#

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.

{
  "EntityRecognizerArn" : "The Amazon Resource Name (ARN) that identifies the entity recognizer currently being trained."
}

tag_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.

{
  "ResourceArn" : "The Amazon Resource Name (ARN) of the given Amazon Comprehend resource to which you want to associate the tags. ",
  "Tags" : [ {
    "Value" : " The second part of a key-value pair that forms a tag associated with a given resource. For instance, if you want to show which resources are used by which departments, you might use “Department” as the initial (key) portion of the pair, with a value of “sales” to indicate the sales department. ",
    "Key" : "The initial part of a key-value pair that forms a tag associated with a given resource. For instance, if you want to show which resources are used by which departments, you might use “Department” as the key portion of the pair, with multiple possible values such as “sales,” “legal,” and “administration.” "
  } ]
}

untag_resource#

Removes a specific tag associated with an Amazon Comprehend resource.

{
  "ResourceArn" : " The Amazon Resource Name (ARN) of the given Amazon Comprehend resource from which you want to remove the tags. ",
  "TagKeys" : [ "string" ]
}