See: newDetectEntities smart constructor.

Create a value of DetectEntities with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:bytes:DetectEntities', detectEntities_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 Text field.

Use the Bytes parameter to input a text, PDF, Word or image file. Using a plain-text file in the Bytes parameter is equivelent to using the Text parameter (the Entities field in the response is identical).

You can also use the Bytes parameter to input an Amazon Textract DetectDocumentText or AnalyzeDocument output file.

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 Bytes parameter, do not use the Text parameter.-- -- Note: This Lens automatically encodes and decodes Base64 data. -- The underlying isomorphism will encode to Base64 representation during -- serialisation, and decode from Base64 representation during deserialisation. -- This Lens accepts and returns only raw unencoded data.

DetectEntities, detectEntities_documentReaderConfig - Provides configuration parameters to override the default actions for extracting text from PDF documents and image files.

DetectEntities, detectEntities_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.

DetectEntities, detectEntities_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.

DetectEntities, detectEntities_text - A UTF-8 text string. The maximum string size is 100 KB. If you enter text using this parameter, do not use the Bytes parameter.

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 Text field.

Use the Bytes parameter to input a text, PDF, Word or image file. Using a plain-text file in the Bytes parameter is equivelent to using the Text parameter (the Entities field in the response is identical).

You can also use the Bytes parameter to input an Amazon Textract DetectDocumentText or AnalyzeDocument output file.

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 Bytes parameter, do not use the Text parameter.-- -- Note: This Lens automatically encodes and decodes Base64 data. -- The underlying isomorphism will encode to Base64 representation during -- serialisation, and decode from Base64 representation during deserialisation. -- This Lens accepts and returns only raw unencoded data.

Provides configuration parameters to override the default actions for extracting text from PDF documents and image files.

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.

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.

A UTF-8 text string. The maximum string size is 100 KB. If you enter text using this parameter, do not use the Bytes parameter.

See: newDetectEntitiesResponse smart constructor.

Create a value of DetectEntitiesResponse with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:blocks:DetectEntitiesResponse', detectEntitiesResponse_blocks - Information about each block of text in the input document. Blocks are nested. A page block contains a block for each line of text, which contains a block for each word.

The Block content for a Word input document does not include a Geometry field.

The Block field is not present in the response for plain-text inputs.

$sel:documentMetadata:DetectEntitiesResponse', detectEntitiesResponse_documentMetadata - Information about the document, discovered during text extraction. This field is present in the response only if your request used the Byte parameter.

DetectEntitiesResponse, detectEntitiesResponse_documentType - The document type for each page in the input document. This field is present in the response only if your request used the Byte parameter.

DetectEntitiesResponse, detectEntitiesResponse_entities - A collection of entities identified in the input text. For each entity, the response provides the entity text, entity type, where the entity text begins and ends, and the level of confidence that Amazon Comprehend has in the detection.

If your request uses a custom entity recognition model, Amazon Comprehend detects the entities that the model is trained to recognize. Otherwise, it detects the default entity types. For a list of default entity types, see Entities in the Comprehend Developer Guide.

$sel:errors:DetectEntitiesResponse', detectEntitiesResponse_errors - Page-level errors that the system detected while processing the input document. The field is empty if the system encountered no errors.

$sel:httpStatus:DetectEntitiesResponse', detectEntitiesResponse_httpStatus - The response's http status code.

Information about each block of text in the input document. Blocks are nested. A page block contains a block for each line of text, which contains a block for each word.

The Block content for a Word input document does not include a Geometry field.

The Block field is not present in the response for plain-text inputs.

Information about the document, discovered during text extraction. This field is present in the response only if your request used the Byte parameter.

The document type for each page in the input document. This field is present in the response only if your request used the Byte parameter.

A collection of entities identified in the input text. For each entity, the response provides the entity text, entity type, where the entity text begins and ends, and the level of confidence that Amazon Comprehend has in the detection.

If your request uses a custom entity recognition model, Amazon Comprehend detects the entities that the model is trained to recognize. Otherwise, it detects the default entity types. For a list of default entity types, see Entities in the Comprehend Developer Guide.

Page-level errors that the system detected while processing the input document. The field is empty if the system encountered no errors.

The response's http status code.