Struct rusoto_comprehend::EntityRecognizerInputDataConfig

pub struct EntityRecognizerInputDataConfig {
    pub annotations: Option<EntityRecognizerAnnotations>,
    pub augmented_manifests: Option<Vec<AugmentedManifestsListItem>>,
    pub data_format: Option<String>,
    pub documents: Option<EntityRecognizerDocuments>,
    pub entity_list: Option<EntityRecognizerEntityList>,
    pub entity_types: Vec<EntityTypesListItem>,
}

Specifies the format and location of the input data.

Fields

annotations: Option<EntityRecognizerAnnotations>

The S3 location of the CSV file that annotates your training documents.

augmented_manifests: Option<Vec<AugmentedManifestsListItem>>

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.

data_format: Option<String>

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.

documents: Option<EntityRecognizerDocuments>

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.

entity_list: Option<EntityRecognizerEntityList>

The S3 location of the CSV file that has the entity list for your custom entity recognizer.

entity_types: Vec<EntityTypesListItem>

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).

Trait Implementations

impl Clone for EntityRecognizerInputDataConfig

fn clone(&self) -> EntityRecognizerInputDataConfig

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for EntityRecognizerInputDataConfig

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for EntityRecognizerInputDataConfig

fn default() -> EntityRecognizerInputDataConfig

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for EntityRecognizerInputDataConfig

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl PartialEq<EntityRecognizerInputDataConfig> for EntityRecognizerInputDataConfig

fn eq(&self, other: &EntityRecognizerInputDataConfig) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &EntityRecognizerInputDataConfig) -> bool

This method tests for !=.

impl Serialize for EntityRecognizerInputDataConfig

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
    __S: Serializer, 

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for EntityRecognizerInputDataConfig