2018/11/16 - Amazon Comprehend - 7 new 2 updated api methods
Changes Amazon Comprehend Custom Classification automatically trains classification models using your text and custom labels.
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.
See also: AWS API Documentation
Request Syntax
client.delete_document_classifier(
DocumentClassifierArn='string'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) that identifies the document classifier.
dict
Response Syntax
{}
Response Structure
(dict) --
Gets a list of the documentation classification jobs that you have submitted.
See also: AWS API Documentation
Request Syntax
client.list_document_classification_jobs(
Filter={
'JobName': 'string',
'JobStatus': 'SUBMITTED'|'IN_PROGRESS'|'COMPLETED'|'FAILED'|'STOP_REQUESTED'|'STOPPED',
'SubmitTimeBefore': datetime(2015, 1, 1),
'SubmitTimeAfter': datetime(2015, 1, 1)
},
NextToken='string',
MaxResults=123
)
dict
Filters the jobs that are returned. You can filter jobs on their names, status, or the date and time that they were submitted. You can only set one filter at a time.
JobName (string) --
Filters on the name of the job.
JobStatus (string) --
Filters the list based on job status. Returns only jobs with the specified status.
SubmitTimeBefore (datetime) --
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.
SubmitTimeAfter (datetime) --
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.
string
Identifies the next page of results to return.
integer
The maximum number of results to return in each page. The default is 100.
dict
Response Syntax
{
'DocumentClassificationJobPropertiesList': [
{
'JobId': 'string',
'JobName': 'string',
'JobStatus': 'SUBMITTED'|'IN_PROGRESS'|'COMPLETED'|'FAILED'|'STOP_REQUESTED'|'STOPPED',
'Message': 'string',
'SubmitTime': datetime(2015, 1, 1),
'EndTime': datetime(2015, 1, 1),
'DocumentClassifierArn': 'string',
'InputDataConfig': {
'S3Uri': 'string',
'InputFormat': 'ONE_DOC_PER_FILE'|'ONE_DOC_PER_LINE'
},
'OutputDataConfig': {
'S3Uri': 'string'
},
'DataAccessRoleArn': 'string'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
DocumentClassificationJobPropertiesList (list) --
A list containing the properties of each job returned.
(dict) --
Provides information about a document classification job.
JobId (string) --
The identifier assigned to the document classification job.
JobName (string) --
The name that you assigned to the document classification job.
JobStatus (string) --
The current status of the document classification job. If the status is FAILED , the Message field shows the reason for the failure.
Message (string) --
A description of the status of the job.
SubmitTime (datetime) --
The time that the document classification job was submitted for processing.
EndTime (datetime) --
The time that the document classification job completed.
DocumentClassifierArn (string) --
The Amazon Resource Name (ARN) that identifies the document classifier.
InputDataConfig (dict) --
The input data configuration that you supplied when you created the document classification job.
S3Uri (string) --
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.
For 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 (string) --
Specifies how the text in an input file should be processed:
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.
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.
OutputDataConfig (dict) --
The output data configuration that you supplied when you created the document classification job.
S3Uri (string) --
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.
When 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.
DataAccessRoleArn (string) --
The Amazon Resource Name (ARN) of the AWS identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data.
NextToken (string) --
Identifies the next page of results to return.
Gets the properties associated with a document classification job. Use this operation to get the status of a classification job.
See also: AWS API Documentation
Request Syntax
client.describe_document_classification_job(
JobId='string'
)
string
[REQUIRED]
The identifier that Amazon Comprehend generated for the job. The operation returns this identifier in its response.
dict
Response Syntax
{
'DocumentClassificationJobProperties': {
'JobId': 'string',
'JobName': 'string',
'JobStatus': 'SUBMITTED'|'IN_PROGRESS'|'COMPLETED'|'FAILED'|'STOP_REQUESTED'|'STOPPED',
'Message': 'string',
'SubmitTime': datetime(2015, 1, 1),
'EndTime': datetime(2015, 1, 1),
'DocumentClassifierArn': 'string',
'InputDataConfig': {
'S3Uri': 'string',
'InputFormat': 'ONE_DOC_PER_FILE'|'ONE_DOC_PER_LINE'
},
'OutputDataConfig': {
'S3Uri': 'string'
},
'DataAccessRoleArn': 'string'
}
}
Response Structure
(dict) --
DocumentClassificationJobProperties (dict) --
An object that describes the properties associated with the document classification job.
JobId (string) --
The identifier assigned to the document classification job.
JobName (string) --
The name that you assigned to the document classification job.
JobStatus (string) --
The current status of the document classification job. If the status is FAILED , the Message field shows the reason for the failure.
Message (string) --
A description of the status of the job.
SubmitTime (datetime) --
The time that the document classification job was submitted for processing.
EndTime (datetime) --
The time that the document classification job completed.
DocumentClassifierArn (string) --
The Amazon Resource Name (ARN) that identifies the document classifier.
InputDataConfig (dict) --
The input data configuration that you supplied when you created the document classification job.
S3Uri (string) --
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.
For 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 (string) --
Specifies how the text in an input file should be processed:
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.
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.
OutputDataConfig (dict) --
The output data configuration that you supplied when you created the document classification job.
S3Uri (string) --
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.
When 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.
DataAccessRoleArn (string) --
The Amazon Resource Name (ARN) of the AWS identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data.
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. After the classifier is trained you can use it to categorize a set of unlabeled documents into those categories.
See also: AWS API Documentation
Request Syntax
client.create_document_classifier(
DocumentClassifierName='string',
DataAccessRoleArn='string',
InputDataConfig={
'S3Uri': 'string'
},
ClientRequestToken='string',
LanguageCode='en'|'es'|'fr'|'de'|'it'|'pt'
)
string
[REQUIRED]
The name of the document classifier.
string
[REQUIRED]
The Amazon Resource Name (ARN) of the AWS Identity and Management (IAM) role that grants Amazon Comprehend read access to your input data.
dict
[REQUIRED]
Specifies the format and location of the input data for the job.
S3Uri (string) -- [REQUIRED]
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.
For 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.
string
A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.
This field is autopopulated if not provided.
string
[REQUIRED]
The language of the input documents. You can create a document classifier in any of the languages supported by Amazon Comprehend. However, all documents must be in the same language.
dict
Response Syntax
{
'DocumentClassifierArn': 'string'
}
Response Structure
(dict) --
DocumentClassifierArn (string) --
The Amazon Resource Name (ARN) that identifies the document classifier.
Gets a list of the document classifiers that you have created.
See also: AWS API Documentation
Request Syntax
client.list_document_classifiers(
Filter={
'Status': 'SUBMITTED'|'TRAINING'|'DELETING'|'IN_ERROR'|'TRAINED',
'SubmitTimeBefore': datetime(2015, 1, 1),
'SubmitTimeAfter': datetime(2015, 1, 1)
},
NextToken='string',
MaxResults=123
)
dict
Filters the jobs that are returned. You can filter jobs on their name, status, or the date and time that they were submitted. You can only set one filter at a time.
Status (string) --
Filters the list of classifiers based on status.
SubmitTimeBefore (datetime) --
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.
SubmitTimeAfter (datetime) --
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.
string
Identifies the next page of results to return.
integer
The maximum number of results to return in each page. The default is 100.
dict
Response Syntax
{
'DocumentClassifierPropertiesList': [
{
'DocumentClassifierArn': 'string',
'LanguageCode': 'en'|'es'|'fr'|'de'|'it'|'pt',
'Status': 'SUBMITTED'|'TRAINING'|'DELETING'|'IN_ERROR'|'TRAINED',
'Message': 'string',
'SubmitTime': datetime(2015, 1, 1),
'EndTime': datetime(2015, 1, 1),
'TrainingStartTime': datetime(2015, 1, 1),
'TrainingEndTime': datetime(2015, 1, 1),
'InputDataConfig': {
'S3Uri': 'string'
},
'ClassifierMetadata': {
'NumberOfLabels': 123,
'NumberOfTrainedDocuments': 123,
'NumberOfTestDocuments': 123,
'EvaluationMetrics': {
'Accuracy': 123.0,
'Precision': 123.0,
'Recall': 123.0,
'F1Score': 123.0
}
},
'DataAccessRoleArn': 'string'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
DocumentClassifierPropertiesList (list) --
A list containing the properties of each job returned.
(dict) --
Provides information about a document classifier.
DocumentClassifierArn (string) --
The Amazon Resource Name (ARN) that identifies the document classifier.
LanguageCode (string) --
The language code for the language of the documents that the classifier was trained on.
Status (string) --
The status of the document classifier. The the status is TRAINED the classifier is ready to use. If the status is FAILED you can see additional information about why the classifier wasn't trained in the Message field.
Message (string) --
Additional information about the status of the classifier.
SubmitTime (datetime) --
The time that the document classifier was submitted for training.
EndTime (datetime) --
The time that training the document classifier completed.
TrainingStartTime (datetime) --
Indicates the time when the training starts on documentation classifiers. You are billed for the time interval between this time and the value of TrainingEndTime.
TrainingEndTime (datetime) --
The time that training of the document classifier was completed. Indicates the time when the training completes on documentation classifiers. You are billed for the time interval between this time and the value of TrainingStartTime.
InputDataConfig (dict) --
The input data configuration that you supplied when you created the document classifier for training.
S3Uri (string) --
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.
For 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.
ClassifierMetadata (dict) --
Information about the document classifier, including the number of documents used for training the classifier, the number of documents used for test the classifier, and an accuracy rating.
NumberOfLabels (integer) --
The number of labels in the input data.
NumberOfTrainedDocuments (integer) --
The number of documents in the input data that were used to train the classifier. Typically this is 80 to 90 percent of the input documents.
NumberOfTestDocuments (integer) --
The number of documents in the input data that were used to test the classifier. Typically this is 10 to 20 percent of the input documents.
EvaluationMetrics (dict) --
Describes the result metrics for the test data associated with an documentation classifier.
Accuracy (float) --
The fraction of the labels that were correct recognized. It is computed by dividing the number of labels in the test documents that were correctly recognized by the total number of labels in the test documents.
Precision (float) --
A measure of the usefulness of the classifier results in the test data. High precision means that the classifier returned substantially more relevant results than irrelevant ones.
Recall (float) --
A measure of how complete the classifier results are for the test data. High recall means that the classifier returned most of the relevant results.
F1Score (float) --
A measure of how accurate the classifier results are for the test data. It is derived from the Precision and Recall values. The F1Score is the harmonic average of the two scores. The highest score is 1, and the worst score is 0.
DataAccessRoleArn (string) --
The Amazon Resource Name (ARN) of the AWS Identity and Management (IAM) role that grants Amazon Comprehend read access to your input data.
NextToken (string) --
Identifies the next page of results to return.
Starts an asynchronous document classification job. Use the operation to track the progress of the job.
See also: AWS API Documentation
Request Syntax
client.start_document_classification_job(
JobName='string',
DocumentClassifierArn='string',
InputDataConfig={
'S3Uri': 'string',
'InputFormat': 'ONE_DOC_PER_FILE'|'ONE_DOC_PER_LINE'
},
OutputDataConfig={
'S3Uri': 'string'
},
DataAccessRoleArn='string',
ClientRequestToken='string'
)
string
The identifier of the job.
string
[REQUIRED]
The Amazon Resource Name (ARN) of the document classifier to use to process the job.
dict
[REQUIRED]
Specifies the format and location of the input data for the job.
S3Uri (string) -- [REQUIRED]
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.
For 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 (string) --
Specifies how the text in an input file should be processed:
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.
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.
dict
[REQUIRED]
Specifies where to send the output files.
S3Uri (string) -- [REQUIRED]
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.
When 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.
string
[REQUIRED]
The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data.
string
A unique identifier for the request. If you do not set the client request token, Amazon Comprehend generates one.
This field is autopopulated if not provided.
dict
Response Syntax
{
'JobId': 'string',
'JobStatus': 'SUBMITTED'|'IN_PROGRESS'|'COMPLETED'|'FAILED'|'STOP_REQUESTED'|'STOPPED'
}
Response Structure
(dict) --
JobId (string) --
The identifier generated for the job. To get the status of the job, use this identifier with the operation.
JobStatus (string) --
The status of the job:
SUBMITTED - The job has been received and queued for processing.
IN_PROGRESS - Amazon Comprehend is processing the job.
COMPLETED - The job was successfully completed and the output is available.
FAILED - The job did not complete. For details, use the operation.
STOP_REQUESTED - Amazon Comprehend has received a stop request for the job and is processing the request.
STOPPED - The job was successfully stopped without completing.
Gets the properties associated with a document classifier.
See also: AWS API Documentation
Request Syntax
client.describe_document_classifier(
DocumentClassifierArn='string'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) that identifies the document classifier. The operation returns this identifier in its response.
dict
Response Syntax
{
'DocumentClassifierProperties': {
'DocumentClassifierArn': 'string',
'LanguageCode': 'en'|'es'|'fr'|'de'|'it'|'pt',
'Status': 'SUBMITTED'|'TRAINING'|'DELETING'|'IN_ERROR'|'TRAINED',
'Message': 'string',
'SubmitTime': datetime(2015, 1, 1),
'EndTime': datetime(2015, 1, 1),
'TrainingStartTime': datetime(2015, 1, 1),
'TrainingEndTime': datetime(2015, 1, 1),
'InputDataConfig': {
'S3Uri': 'string'
},
'ClassifierMetadata': {
'NumberOfLabels': 123,
'NumberOfTrainedDocuments': 123,
'NumberOfTestDocuments': 123,
'EvaluationMetrics': {
'Accuracy': 123.0,
'Precision': 123.0,
'Recall': 123.0,
'F1Score': 123.0
}
},
'DataAccessRoleArn': 'string'
}
}
Response Structure
(dict) --
DocumentClassifierProperties (dict) --
An object that contains the properties associated with a document classifier.
DocumentClassifierArn (string) --
The Amazon Resource Name (ARN) that identifies the document classifier.
LanguageCode (string) --
The language code for the language of the documents that the classifier was trained on.
Status (string) --
The status of the document classifier. The the status is TRAINED the classifier is ready to use. If the status is FAILED you can see additional information about why the classifier wasn't trained in the Message field.
Message (string) --
Additional information about the status of the classifier.
SubmitTime (datetime) --
The time that the document classifier was submitted for training.
EndTime (datetime) --
The time that training the document classifier completed.
TrainingStartTime (datetime) --
Indicates the time when the training starts on documentation classifiers. You are billed for the time interval between this time and the value of TrainingEndTime.
TrainingEndTime (datetime) --
The time that training of the document classifier was completed. Indicates the time when the training completes on documentation classifiers. You are billed for the time interval between this time and the value of TrainingStartTime.
InputDataConfig (dict) --
The input data configuration that you supplied when you created the document classifier for training.
S3Uri (string) --
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.
For 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.
ClassifierMetadata (dict) --
Information about the document classifier, including the number of documents used for training the classifier, the number of documents used for test the classifier, and an accuracy rating.
NumberOfLabels (integer) --
The number of labels in the input data.
NumberOfTrainedDocuments (integer) --
The number of documents in the input data that were used to train the classifier. Typically this is 80 to 90 percent of the input documents.
NumberOfTestDocuments (integer) --
The number of documents in the input data that were used to test the classifier. Typically this is 10 to 20 percent of the input documents.
EvaluationMetrics (dict) --
Describes the result metrics for the test data associated with an documentation classifier.
Accuracy (float) --
The fraction of the labels that were correct recognized. It is computed by dividing the number of labels in the test documents that were correctly recognized by the total number of labels in the test documents.
Precision (float) --
A measure of the usefulness of the classifier results in the test data. High precision means that the classifier returned substantially more relevant results than irrelevant ones.
Recall (float) --
A measure of how complete the classifier results are for the test data. High recall means that the classifier returned most of the relevant results.
F1Score (float) --
A measure of how accurate the classifier results are for the test data. It is derived from the Precision and Recall values. The F1Score is the harmonic average of the two scores. The highest score is 1, and the worst score is 0.
DataAccessRoleArn (string) --
The Amazon Resource Name (ARN) of the AWS Identity and Management (IAM) role that grants Amazon Comprehend read access to your input data.
{'ResultList': {'SyntaxTokens': {'PartOfSpeech': {'Tag': {'CCONJ'}}}}}
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.
See also: AWS API Documentation
Request Syntax
client.batch_detect_syntax(
TextList=[
'string',
],
LanguageCode='en'|'es'|'fr'|'de'|'it'|'pt'
)
list
[REQUIRED]
A list containing the text of the input documents. The list can contain a maximum of 25 documents. Each document must contain fewer that 5,000 bytes of UTF-8 encoded characters.
(string) --
string
[REQUIRED]
The language of the input documents. You can specify English ("en") or Spanish ("es"). All documents must be in the same language.
dict
Response Syntax
{
'ResultList': [
{
'Index': 123,
'SyntaxTokens': [
{
'TokenId': 123,
'Text': 'string',
'BeginOffset': 123,
'EndOffset': 123,
'PartOfSpeech': {
'Tag': 'ADJ'|'ADP'|'ADV'|'AUX'|'CONJ'|'CCONJ'|'DET'|'INTJ'|'NOUN'|'NUM'|'O'|'PART'|'PRON'|'PROPN'|'PUNCT'|'SCONJ'|'SYM'|'VERB',
'Score': ...
}
},
]
},
],
'ErrorList': [
{
'Index': 123,
'ErrorCode': 'string',
'ErrorMessage': 'string'
},
]
}
Response Structure
(dict) --
ResultList (list) --
A list of objects containing the results of the operation. The results are sorted in ascending order by the Index field and match the order of the documents in the input list. If all of the documents contain an error, the ResultList is empty.
(dict) --
The result of calling the operation. The operation returns one object that is successfully processed by the operation.
Index (integer) --
The zero-based index of the document in the input list.
SyntaxTokens (list) --
The syntax tokens for the words in the document, one token for each word.
(dict) --
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.
TokenId (integer) --
A unique identifier for a token.
Text (string) --
The word that was recognized in the source text.
BeginOffset (integer) --
The zero-based offset from the beginning of the source text to the first character in the word.
EndOffset (integer) --
The zero-based offset from the beginning of the source text to the last character in the word.
PartOfSpeech (dict) --
Provides the part of speech label and the confidence level that Amazon Comprehend has that the part of speech was correctly identified. For more information, see how-syntax.
Tag (string) --
Identifies the part of speech that the token represents.
Score (float) --
The confidence that Amazon Comprehend has that the part of speech was correctly identified.
ErrorList (list) --
A list containing one object for each document that contained an error. The results are sorted in ascending order by the Index field and match the order of the documents in the input list. If there are no errors in the batch, the ErrorList is empty.
(dict) --
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.
Index (integer) --
The zero-based index of the document in the input list.
ErrorCode (string) --
The numeric error code of the error.
ErrorMessage (string) --
A text description of the error.
{'SyntaxTokens': {'PartOfSpeech': {'Tag': {'CCONJ'}}}}
Inspects text for syntax and the part of speech of words in the document. For more information, how-syntax.
See also: AWS API Documentation
Request Syntax
client.detect_syntax(
Text='string',
LanguageCode='en'|'es'|'fr'|'de'|'it'|'pt'
)
string
[REQUIRED]
A UTF-8 string. Each string must contain fewer that 5,000 bytes of UTF encoded characters.
string
[REQUIRED]
The language code of the input documents. You can specify English ("en") or Spanish ("es").
dict
Response Syntax
{
'SyntaxTokens': [
{
'TokenId': 123,
'Text': 'string',
'BeginOffset': 123,
'EndOffset': 123,
'PartOfSpeech': {
'Tag': 'ADJ'|'ADP'|'ADV'|'AUX'|'CONJ'|'CCONJ'|'DET'|'INTJ'|'NOUN'|'NUM'|'O'|'PART'|'PRON'|'PROPN'|'PUNCT'|'SCONJ'|'SYM'|'VERB',
'Score': ...
}
},
]
}
Response Structure
(dict) --
SyntaxTokens (list) --
A collection of syntax tokens describing the text. For each token, the response provides the text, the token type, where the text begins and ends, and the level of confidence that Amazon Comprehend has that the token is correct. For a list of token types, see how-syntax.
(dict) --
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.
TokenId (integer) --
A unique identifier for a token.
Text (string) --
The word that was recognized in the source text.
BeginOffset (integer) --
The zero-based offset from the beginning of the source text to the first character in the word.
EndOffset (integer) --
The zero-based offset from the beginning of the source text to the last character in the word.
PartOfSpeech (dict) --
Provides the part of speech label and the confidence level that Amazon Comprehend has that the part of speech was correctly identified. For more information, see how-syntax.
Tag (string) --
Identifies the part of speech that the token represents.
Score (float) --
The confidence that Amazon Comprehend has that the part of speech was correctly identified.