View source: R/comprehend_operations.R
comprehend_detect_entities | R Documentation |
Detects named entities in input text when you use the pre-trained model. Detects custom entities if you have a custom entity recognition model.
See https://www.paws-r-sdk.com/docs/comprehend_detect_entities/ for full documentation.
comprehend_detect_entities(
Text = NULL,
LanguageCode = NULL,
EndpointArn = NULL,
Bytes = NULL,
DocumentReaderConfig = NULL
)
Text |
A UTF-8 text string. The maximum string size is 100 KB. If you enter
text using this parameter, do not use the |
LanguageCode |
The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend. If your request includes the endpoint for a custom entity recognition model, Amazon Comprehend uses the language of your custom model, and it ignores any language code that you specify here. All input documents must be in the same language. |
EndpointArn |
The Amazon Resource Name of an endpoint that is associated with a custom entity recognition model. Provide an endpoint if you want to detect entities by using your own custom model instead of the default model that is used by Amazon Comprehend. If you specify an endpoint, Amazon Comprehend uses the language of your custom model, and it ignores any language code that you provide in your request. For information about endpoints, see Managing endpoints. |
Bytes |
This field applies only when you use a custom entity recognition model
that was trained with PDF annotations. For other cases, enter your text
input in the Use the You can also use the Provide the input document as a sequence of base64-encoded bytes. If your code uses an Amazon Web Services SDK to detect entities, the SDK may encode the document file bytes for you. The maximum length of this field depends on the input document type. For details, see Inputs for real-time custom analysis in the Comprehend Developer Guide. If you use the |
DocumentReaderConfig |
Provides configuration parameters to override the default actions for extracting text from PDF documents and image files. |
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