A project is a container that houses all of your labeling operations for a specific set of data rows.
Ideally, each project is highly customized to create a specifically labeled dataset. For example, you may create a separate project for each of the following situations:
You've identified an edge case that your model struggles to predict and you only need to label the Data Rows that contain that specific edge case.
You need a large amount of training data and it is too much work for one labeling team. You can create separate projects that reference the same ontology and distribute the labeling work across multiple teams.
You have highly specialized labeling teams that are trained to annotate specific data modalities (e.g., images and text). In this case, you can create separate projects and tailor the ontology to label those data types specifically.
The project is where the ontology, the data rows, and the editor interface connect. Projects are designed to make your labeling operations as efficient as possible.
Updated 16 days ago