Describes the documents submitted with a dataset for an entity recognizer model.
Type: objectProperties: 2Required: 1
Machine-LearningNatural Language ProcessingNLPText Analysis
DatasetEntityRecognizerDocuments is a JSON Structure definition published by Amazon Comprehend, describing 2 properties, of which 1 is required. It conforms to the https://json-structure.org/meta/core/v0/# meta-schema.
{
"$schema": "https://json-structure.org/meta/core/v0/#",
"$id": "https://raw.githubusercontent.com/api-evangelist/amazon-comprehend/refs/heads/main/json-structure/openapi.yml-dataset-entity-recognizer-documents-structure.json",
"name": "DatasetEntityRecognizerDocuments",
"description": "Describes the documents submitted with a dataset for an entity recognizer model.",
"type": "object",
"properties": {
"S3Uri": {
"allOf": [
{
"$ref": "#/components/schemas/S3Uri"
},
{
"description": " Specifies the Amazon S3 location where the documents for the dataset are located. "
}
]
},
"InputFormat": {
"allOf": [
{
"$ref": "#/components/schemas/InputFormat"
},
{
"description": " Specifies how the text in an input file should be processed. This is optional, and the default is ONE_DOC_PER_LINE. 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."
}
]
}
},
"required": [
"S3Uri"
]
}
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