Label Studio Enterprise now has comments! Communication between labelers and managers is often one of the stickiest points in the dataset development lifecycle. When labelers have questions about a specific task, it can be difficult to get a timely answer. And when a labeler makes an error on a task, it can be difficult for managers and administrators to give relevant and specific feedback so that the annotator can improve.
That’s why we’ve added commenting to Label Studio.
With this new feature:
Comments enables you to deliver increased labeler efficiency and higher annotation quality.
For more information, check out our detailed guide. If you want to try comments out for yourself, try our 14-day free trial.
Annotator Performance Dashboards make it easer to manage labeling teams at scale and orchestrate all the internal and external resources needed to improve data quality, without sacrificing speed.
In this post, we’ll guide you through the process of using Prompts in Label Studio Enterprise to pre-annotate data for Named Entity Recognition (NER) tasks.
Learn the intricacies of data quality, strategies to build the data you need for training and fine-tuning ML/AI models, and how you can use Label Studio Enterprise to engineer your AI/ML success.
