Reviewing Labels is an essential step in the process of training data management to ensure only the highest quality data is going to train your machine learning model. Without reviewing the quality of your labeled data, you risk letting poor annotations slip through the cracks which can degrade the performance of your model.
Reviewing labels starts from the Activity tab. From here you can view all label activity and enter Review Mode by clicking on the desired label to review.
Modifying/editing an existing label in Review Mode is the same environment as the labeling environment. You simply click on the label you want to review and the labeling environment will be available to make any necessary improvements to the annotations.
There are different ways to prioritize which labels to review. You can filter the labels in the Activity tab based on who the labeler is, which dataset the labels came from, or based on the Consensus score.