Fundamental elements of the Labelbox editor

Aligning with your team on key terms used in Labelbox will serve to greatly enhance collaboration and cohesiveness throughout your work in the platform. In this brief video, we introduce the fundamental elements of the Labelbox editor.

For a complete list of key definitions, check out our documentation here.

  • Annotation: An instance of a Feature. Annotations can be imported as ground truth, model predictions, or can be created in the Labelbox editor. Annotations are categorized as Objects (e.g. bounding box, polygon, etc) or Classifications (e.g. radio, checklist, etc).
  • Asset: A single cloud-hosted file to be labeled (e.g., an image, a video, or a text file).
  • Data Row: The container that houses all of the following information for a single Asset:

URL to your cloud-hosted file


Media attributes (e.g data type, size, etc.)

Attachments (files that provide context for your labelers)

  • Editor: The labeling interface you can use to create, review, and edit annotations. When you create a project, you will be prompted to configure your editor (i.e., select an ontology, add labeling instructions, etc).
  • Feature: A feature is the master definition of what you want the model to predict. It is also the blueprint for your ground truth. An ontology is made up of a set of features. There are two kinds of features: objects (e.g., Bounding box) and classifications (e.g., Radio). A feature can have multiple deeply nested sub-classifications.
  • Label: A collection of all annotations on a Data Row. For example, all Bounding boxes, Polylines, and Radio classifications on an image would be considered the “Label”.
  • Ontology: A collection of Features and their relationships (also known as a taxonomy). Ontologies can be reused across different projects. It is essential for data labeling, model training, and evaluation. When you are in the editor, the ontology is what appears in the “Tools” panel.