steplabeled
Steplabeled is a labeling approach in which annotations are attached to discrete steps within a sequence or process, rather than to individual time points or objects. Each step is assigned a label that describes its category, action, or status, and the ordering of steps is preserved.
In steplabeled datasets, the unit of annotation is the step, and the label taxonomy defines the set
Common applications include process mining and workflow analytics, instructional design, and activity recognition in robotics or
Advantages of steplabeled data include easier auditability, improved alignment with domain expertise, and resilience to temporal
Steplabeled is related to, but distinct from, frame-level labeling, event segmentation, and sequence tagging. It is