SageMaker Ground Truth Labeling Job

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SageMaker Ground Truth Labeling Job is an AWS resource that manages data labeling tasks for machine learning. It allows you to create and monitor labeling jobs where human labelers or automated processes annotate datasets. The service supports workflows for images, text, video, and other data types, and integrates with workforce options such as Amazon Mechanical Turk, vendor workforces, or your own private team. This resource provides details about the labeling job’s status, input and output data locations, and configuration settings, helping streamline the preparation of high-quality training data for machine learning models.

aws.sagemaker_labeling_job

Fields

ID	Type	Data Type	Description
_key	core	string
account_id	core	string
creation_time	core	timestamp	The date and time that the labeling job was created.
failure_reason	core	string	If the job failed, the reason that it failed.
human_task_config	core	json	Configuration information required for human workers to complete a labeling task.
input_config	core	json	Input configuration information for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
job_reference_code	core	string	A unique identifier for work done as part of a labeling job.
label_attribute_name	core	string	The attribute used as the label in the output manifest file.
label_category_config_s3_uri	core	string	The S3 location of the JSON file that defines the categories used to label data objects. Please note the following label-category limits: Semantic segmentation labeling jobs using automated labeling: 20 labels Box bounding labeling jobs (all): 10 labels The file is a JSON structure in the following format: { "document-version": "2018-11-28" "labels": [ { "label": "label 1" }, { "label": "label 2" }, ... { "label": "label n" } ] }
label_counters	core	json	Provides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn't be labeled, and the total number of objects labeled.
labeling_job_algorithms_config	core	json	Configuration information for automated data labeling.
labeling_job_arn	core	string	The Amazon Resource Name (ARN) of the labeling job.
labeling_job_name	core	string	The name assigned to the labeling job when it was created.
labeling_job_output	core	json	The location of the output produced by the labeling job.
labeling_job_status	core	string	The processing status of the labeling job.
last_modified_time	core	timestamp	The date and time that the labeling job was last updated.
output_config	core	json	The location of the job's output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
role_arn	core	string	The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during data labeling.
stopping_conditions	core	json	A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped.
tags	core	hstore