Ensuring annotation quality and dataset balance
Maintaining high annotation quality and target class balance requires diligent management. In this section, we’ll look at some techniques that can help assure labeling quality.
Assess annotator skills
It is highly recommended that annotators undergo thorough training sessions and complete qualification tests before they can work independently. This ensures that they have a solid foundation of knowledge and understanding in their respective tasks. These performance metrics can be visualized in the labeling platform when the reviewers accept or reject annotations. If a labeler has many rejected annotations, it is necessary to ensure that they understand the task and assess what help can be provided to them.
It is advisable to periodically assess the labeler’s skills by providing control samples for evaluation purposes. This ongoing evaluation helps maintain the quality and consistency of their work over time.
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