EntityRecognizerInputDataConfig (AWS SDK for Java

java.lang.Object
- com.amazonaws.services.comprehend.model.EntityRecognizerInputDataConfig

All Implemented Interfaces:: StructuredPojo, Serializable, Cloneable

@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class EntityRecognizerInputDataConfig
extends Object
implements Serializable, Cloneable, StructuredPojo

Specifies the format and location of the input data.

See Also:: AWS API Documentation, Serialized Form

Constructor Summary

Constructors
Constructor and Description

EntityRecognizerInputDataConfig()

Constructors
Constructor and Description
`EntityRecognizerInputDataConfig()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`EntityRecognizerInputDataConfig`	`clone()`
`boolean`	`equals(Object obj)`
`EntityRecognizerAnnotations`	`getAnnotations()` The S3 location of the CSV file that annotates your training documents.
`List<AugmentedManifestsListItem>`	`getAugmentedManifests()` A list of augmented manifest files that provide training data for your custom model.
`String`	`getDataFormat()` The format of your training data:
`EntityRecognizerDocuments`	`getDocuments()` The S3 location of the folder that contains the training documents for your custom entity recognizer.
`EntityRecognizerEntityList`	`getEntityList()` The S3 location of the CSV file that has the entity list for your custom entity recognizer.
`List<EntityTypesListItem>`	`getEntityTypes()` The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer.
`int`	`hashCode()`
`void`	`marshall(ProtocolMarshaller protocolMarshaller)` Marshalls this structured data using the given `ProtocolMarshaller`.
`void`	`setAnnotations(EntityRecognizerAnnotations annotations)` The S3 location of the CSV file that annotates your training documents.
`void`	`setAugmentedManifests(Collection<AugmentedManifestsListItem> augmentedManifests)` A list of augmented manifest files that provide training data for your custom model.
`void`	`setDataFormat(String dataFormat)` The format of your training data:
`void`	`setDocuments(EntityRecognizerDocuments documents)` The S3 location of the folder that contains the training documents for your custom entity recognizer.
`void`	`setEntityList(EntityRecognizerEntityList entityList)` The S3 location of the CSV file that has the entity list for your custom entity recognizer.
`void`	`setEntityTypes(Collection<EntityTypesListItem> entityTypes)` The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer.
`String`	`toString()` Returns a string representation of this object.
`EntityRecognizerInputDataConfig`	`withAnnotations(EntityRecognizerAnnotations annotations)` The S3 location of the CSV file that annotates your training documents.
`EntityRecognizerInputDataConfig`	`withAugmentedManifests(AugmentedManifestsListItem... augmentedManifests)` A list of augmented manifest files that provide training data for your custom model.
`EntityRecognizerInputDataConfig`	`withAugmentedManifests(Collection<AugmentedManifestsListItem> augmentedManifests)` A list of augmented manifest files that provide training data for your custom model.
`EntityRecognizerInputDataConfig`	`withDataFormat(EntityRecognizerDataFormat dataFormat)` The format of your training data:
`EntityRecognizerInputDataConfig`	`withDataFormat(String dataFormat)` The format of your training data:
`EntityRecognizerInputDataConfig`	`withDocuments(EntityRecognizerDocuments documents)` The S3 location of the folder that contains the training documents for your custom entity recognizer.
`EntityRecognizerInputDataConfig`	`withEntityList(EntityRecognizerEntityList entityList)` The S3 location of the CSV file that has the entity list for your custom entity recognizer.
`EntityRecognizerInputDataConfig`	`withEntityTypes(Collection<EntityTypesListItem> entityTypes)` The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer.
`EntityRecognizerInputDataConfig`	`withEntityTypes(EntityTypesListItem... entityTypes)` The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer.

Methods inherited from class java.lang.Object
getClass, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - EntityRecognizerInputDataConfig
```
public EntityRecognizerInputDataConfig()
```
- Method Detail
  - setDataFormat
```
public void setDataFormat(String dataFormat)
```
    The format of your training data:
    - COMPREHEND_CSV: A CSV file that supplements your training documents. The CSV file contains information about the custom entities that your trained model will detect. The required format of the file depends on whether you are providing annotations or an entity list.
      
      If you use this value, you must provide your CSV file by using either the Annotations or EntityList parameters. You must provide your training documents by using the Documents parameter.
    - AUGMENTED_MANIFEST: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its labels. Each label annotates a named entity in the training document.
      
      If you use this value, you must provide the AugmentedManifests parameter in your request.
    If you don't specify a value, Amazon Comprehend uses COMPREHEND_CSV as the default.
    Parameters:
    dataFormat - The format of your training data:
    
    COMPREHEND_CSV: A CSV file that supplements your training documents. The CSV file contains information about the custom entities that your trained model will detect. The required format of the file depends on whether you are providing annotations or an entity list.
    
    If you use this value, you must provide your CSV file by using either the Annotations or EntityList parameters. You must provide your training documents by using the Documents parameter.
    
    AUGMENTED_MANIFEST: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its labels. Each label annotates a named entity in the training document.
    
    If you use this value, you must provide the AugmentedManifests parameter in your request.
    
    If you don't specify a value, Amazon Comprehend uses COMPREHEND_CSV as the default.
    See Also:
    
    EntityRecognizerDataFormat
  - getDataFormat
```
public String getDataFormat()
```
    The format of your training data:
    - COMPREHEND_CSV: A CSV file that supplements your training documents. The CSV file contains information about the custom entities that your trained model will detect. The required format of the file depends on whether you are providing annotations or an entity list.
      
      If you use this value, you must provide your CSV file by using either the Annotations or EntityList parameters. You must provide your training documents by using the Documents parameter.
    - AUGMENTED_MANIFEST: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its labels. Each label annotates a named entity in the training document.
      
      If you use this value, you must provide the AugmentedManifests parameter in your request.
    If you don't specify a value, Amazon Comprehend uses COMPREHEND_CSV as the default.
    Returns:
    The format of your training data:
    
    COMPREHEND_CSV: A CSV file that supplements your training documents. The CSV file contains information about the custom entities that your trained model will detect. The required format of the file depends on whether you are providing annotations or an entity list.
    
    If you use this value, you must provide your CSV file by using either the Annotations or EntityList parameters. You must provide your training documents by using the Documents parameter.
    
    AUGMENTED_MANIFEST: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its labels. Each label annotates a named entity in the training document.
    
    If you use this value, you must provide the AugmentedManifests parameter in your request.
    
    If you don't specify a value, Amazon Comprehend uses COMPREHEND_CSV as the default.
    See Also:
    
    EntityRecognizerDataFormat
  - withDataFormat
```
public EntityRecognizerInputDataConfig withDataFormat(String dataFormat)
```
    The format of your training data:
    - COMPREHEND_CSV: A CSV file that supplements your training documents. The CSV file contains information about the custom entities that your trained model will detect. The required format of the file depends on whether you are providing annotations or an entity list.
      
      If you use this value, you must provide your CSV file by using either the Annotations or EntityList parameters. You must provide your training documents by using the Documents parameter.
    - AUGMENTED_MANIFEST: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its labels. Each label annotates a named entity in the training document.
      
      If you use this value, you must provide the AugmentedManifests parameter in your request.
    If you don't specify a value, Amazon Comprehend uses COMPREHEND_CSV as the default.
    Parameters:
    dataFormat - The format of your training data:
    
    COMPREHEND_CSV: A CSV file that supplements your training documents. The CSV file contains information about the custom entities that your trained model will detect. The required format of the file depends on whether you are providing annotations or an entity list.
    
    If you use this value, you must provide your CSV file by using either the Annotations or EntityList parameters. You must provide your training documents by using the Documents parameter.
    
    AUGMENTED_MANIFEST: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its labels. Each label annotates a named entity in the training document.
    
    If you use this value, you must provide the AugmentedManifests parameter in your request.
    
    If you don't specify a value, Amazon Comprehend uses COMPREHEND_CSV as the default.
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    EntityRecognizerDataFormat
  - withDataFormat
```
public EntityRecognizerInputDataConfig withDataFormat(EntityRecognizerDataFormat dataFormat)
```
    The format of your training data:
    - COMPREHEND_CSV: A CSV file that supplements your training documents. The CSV file contains information about the custom entities that your trained model will detect. The required format of the file depends on whether you are providing annotations or an entity list.
      
      If you use this value, you must provide your CSV file by using either the Annotations or EntityList parameters. You must provide your training documents by using the Documents parameter.
    - AUGMENTED_MANIFEST: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its labels. Each label annotates a named entity in the training document.
      
      If you use this value, you must provide the AugmentedManifests parameter in your request.
    If you don't specify a value, Amazon Comprehend uses COMPREHEND_CSV as the default.
    Parameters:
    dataFormat - The format of your training data:
    
    COMPREHEND_CSV: A CSV file that supplements your training documents. The CSV file contains information about the custom entities that your trained model will detect. The required format of the file depends on whether you are providing annotations or an entity list.
    
    If you use this value, you must provide your CSV file by using either the Annotations or EntityList parameters. You must provide your training documents by using the Documents parameter.
    
    AUGMENTED_MANIFEST: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its labels. Each label annotates a named entity in the training document.
    
    If you use this value, you must provide the AugmentedManifests parameter in your request.
    
    If you don't specify a value, Amazon Comprehend uses COMPREHEND_CSV as the default.
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    EntityRecognizerDataFormat
  - getEntityTypes
```
public List<EntityTypesListItem> getEntityTypes()
```
    The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer. Any entity types that you don't specify are ignored.
    
    A maximum of 25 entity types can be used at one time to train an entity recognizer. Entity types must not contain the following invalid characters: \n (line break), \\n (escaped line break), \r (carriage return), \\r (escaped carriage return), \t (tab), \\t (escaped tab), space, and , (comma).
    
    Returns:
    
    The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer. Any entity types that you don't specify are ignored.
    
    A maximum of 25 entity types can be used at one time to train an entity recognizer. Entity types must not contain the following invalid characters: \n (line break), \\n (escaped line break), \r (carriage return), \\r (escaped carriage return), \t (tab), \\t (escaped tab), space, and , (comma).
  - setEntityTypes
```
public void setEntityTypes(Collection<EntityTypesListItem> entityTypes)
```
    The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer. Any entity types that you don't specify are ignored.
    
    A maximum of 25 entity types can be used at one time to train an entity recognizer. Entity types must not contain the following invalid characters: \n (line break), \\n (escaped line break), \r (carriage return), \\r (escaped carriage return), \t (tab), \\t (escaped tab), space, and , (comma).
    
    Parameters:
    
    entityTypes - The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer. Any entity types that you don't specify are ignored.
    
    A maximum of 25 entity types can be used at one time to train an entity recognizer. Entity types must not contain the following invalid characters: \n (line break), \\n (escaped line break), \r (carriage return), \\r (escaped carriage return), \t (tab), \\t (escaped tab), space, and , (comma).
  - withEntityTypes
```
public EntityRecognizerInputDataConfig withEntityTypes(EntityTypesListItem... entityTypes)
```
    The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer. Any entity types that you don't specify are ignored.
    
    A maximum of 25 entity types can be used at one time to train an entity recognizer. Entity types must not contain the following invalid characters: \n (line break), \\n (escaped line break), \r (carriage return), \\r (escaped carriage return), \t (tab), \\t (escaped tab), space, and , (comma).
    
    NOTE: This method appends the values to the existing list (if any). Use setEntityTypes(java.util.Collection) or withEntityTypes(java.util.Collection) if you want to override the existing values.
    
    Parameters:
    
    entityTypes - The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer. Any entity types that you don't specify are ignored.
    
    A maximum of 25 entity types can be used at one time to train an entity recognizer. Entity types must not contain the following invalid characters: \n (line break), \\n (escaped line break), \r (carriage return), \\r (escaped carriage return), \t (tab), \\t (escaped tab), space, and , (comma).
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - withEntityTypes
```
public EntityRecognizerInputDataConfig withEntityTypes(Collection<EntityTypesListItem> entityTypes)
```
    The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer. Any entity types that you don't specify are ignored.
    
    A maximum of 25 entity types can be used at one time to train an entity recognizer. Entity types must not contain the following invalid characters: \n (line break), \\n (escaped line break), \r (carriage return), \\r (escaped carriage return), \t (tab), \\t (escaped tab), space, and , (comma).
    
    Parameters:
    
    entityTypes - The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer. Any entity types that you don't specify are ignored.
    
    A maximum of 25 entity types can be used at one time to train an entity recognizer. Entity types must not contain the following invalid characters: \n (line break), \\n (escaped line break), \r (carriage return), \\r (escaped carriage return), \t (tab), \\t (escaped tab), space, and , (comma).
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setDocuments
```
public void setDocuments(EntityRecognizerDocuments documents)
```
    The S3 location of the folder that contains the training documents for your custom entity recognizer.
    
    This parameter is required if you set DataFormat to COMPREHEND_CSV.
    
    Parameters:
    
    documents - The S3 location of the folder that contains the training documents for your custom entity recognizer.
    
    This parameter is required if you set DataFormat to COMPREHEND_CSV.
  - getDocuments
```
public EntityRecognizerDocuments getDocuments()
```
    The S3 location of the folder that contains the training documents for your custom entity recognizer.
    
    This parameter is required if you set DataFormat to COMPREHEND_CSV.
    
    Returns:
    
    The S3 location of the folder that contains the training documents for your custom entity recognizer.
    
    This parameter is required if you set DataFormat to COMPREHEND_CSV.
  - withDocuments
```
public EntityRecognizerInputDataConfig withDocuments(EntityRecognizerDocuments documents)
```
    The S3 location of the folder that contains the training documents for your custom entity recognizer.
    
    This parameter is required if you set DataFormat to COMPREHEND_CSV.
    
    Parameters:
    
    documents - The S3 location of the folder that contains the training documents for your custom entity recognizer.
    
    This parameter is required if you set DataFormat to COMPREHEND_CSV.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setAnnotations
```
public void setAnnotations(EntityRecognizerAnnotations annotations)
```
    The S3 location of the CSV file that annotates your training documents.
    
    Parameters:
    
    annotations - The S3 location of the CSV file that annotates your training documents.
  - getAnnotations
```
public EntityRecognizerAnnotations getAnnotations()
```
    The S3 location of the CSV file that annotates your training documents.
    
    Returns:
    
    The S3 location of the CSV file that annotates your training documents.
  - withAnnotations
```
public EntityRecognizerInputDataConfig withAnnotations(EntityRecognizerAnnotations annotations)
```
    The S3 location of the CSV file that annotates your training documents.
    
    Parameters:
    
    annotations - The S3 location of the CSV file that annotates your training documents.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setEntityList
```
public void setEntityList(EntityRecognizerEntityList entityList)
```
    The S3 location of the CSV file that has the entity list for your custom entity recognizer.
    
    Parameters:
    
    entityList - The S3 location of the CSV file that has the entity list for your custom entity recognizer.
  - getEntityList
```
public EntityRecognizerEntityList getEntityList()
```
    The S3 location of the CSV file that has the entity list for your custom entity recognizer.
    
    Returns:
    
    The S3 location of the CSV file that has the entity list for your custom entity recognizer.
  - withEntityList
```
public EntityRecognizerInputDataConfig withEntityList(EntityRecognizerEntityList entityList)
```
    The S3 location of the CSV file that has the entity list for your custom entity recognizer.
    
    Parameters:
    
    entityList - The S3 location of the CSV file that has the entity list for your custom entity recognizer.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - getAugmentedManifests
```
public List<AugmentedManifestsListItem> getAugmentedManifests()
```
    A list of augmented manifest files that provide training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.
    
    This parameter is required if you set DataFormat to AUGMENTED_MANIFEST.
    
    Returns:
    
    A list of augmented manifest files that provide training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.
    
    This parameter is required if you set DataFormat to AUGMENTED_MANIFEST.
  - setAugmentedManifests
```
public void setAugmentedManifests(Collection<AugmentedManifestsListItem> augmentedManifests)
```
    A list of augmented manifest files that provide training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.
    
    This parameter is required if you set DataFormat to AUGMENTED_MANIFEST.
    
    Parameters:
    
    augmentedManifests - A list of augmented manifest files that provide training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.
    
    This parameter is required if you set DataFormat to AUGMENTED_MANIFEST.
  - withAugmentedManifests
```
public EntityRecognizerInputDataConfig withAugmentedManifests(AugmentedManifestsListItem... augmentedManifests)
```
    A list of augmented manifest files that provide training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.
    
    This parameter is required if you set DataFormat to AUGMENTED_MANIFEST.
    
    NOTE: This method appends the values to the existing list (if any). Use setAugmentedManifests(java.util.Collection) or withAugmentedManifests(java.util.Collection) if you want to override the existing values.
    
    Parameters:
    
    augmentedManifests - A list of augmented manifest files that provide training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.
    
    This parameter is required if you set DataFormat to AUGMENTED_MANIFEST.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - withAugmentedManifests
```
public EntityRecognizerInputDataConfig withAugmentedManifests(Collection<AugmentedManifestsListItem> augmentedManifests)
```
    A list of augmented manifest files that provide training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.
    
    This parameter is required if you set DataFormat to AUGMENTED_MANIFEST.
    
    Parameters:
    
    augmentedManifests - A list of augmented manifest files that provide training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.
    
    This parameter is required if you set DataFormat to AUGMENTED_MANIFEST.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - toString
```
public String toString()
```
    Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    
    A string representation of this object.
    
    See Also:
    
    Object.toString()
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class Object
  - clone
```
public EntityRecognizerInputDataConfig clone()
```
    Overrides:
    
    clone in class Object
  - marshall
```
public void marshall(ProtocolMarshaller protocolMarshaller)
```
    Description copied from interface: StructuredPojo
    
    Marshalls this structured data using the given ProtocolMarshaller.
    
    Specified by:
    
    marshall in interface StructuredPojo
    
    Parameters:
    
    protocolMarshaller - Implementation of ProtocolMarshaller used to marshall this object's data.

AWS SDK for Java 1.x API Reference - 1.12.773

Class EntityRecognizerInputDataConfig

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

EntityRecognizerInputDataConfig

Method Detail

setDataFormat

getDataFormat

withDataFormat

withDataFormat

getEntityTypes

setEntityTypes

withEntityTypes

withEntityTypes

setDocuments

getDocuments

withDocuments

setAnnotations

getAnnotations

withAnnotations

setEntityList

getEntityList

withEntityList

getAugmentedManifests

setAugmentedManifests

withAugmentedManifests

withAugmentedManifests

toString

equals

hashCode

clone

marshall