Data Annotation vs Data Labeling (vs Data Tagging)

Data annotation and data labeling mostly mean the same thing: adding information to raw data so a machine learning system can learn from it or be evaluated against it. When people distinguish them, "labeling" usually means assigning a category to a whole item, and "annotation" means marking up parts of it, like boxes around objects or highlighted spans of text.

How the terms are usually used

Data labeling tends to mean one answer per item. This email is spam. This review is positive. This ticket goes to billing.

Data annotation tends to mean richer markup inside an item. A bounding box around each car in an image, the span of text that names a company, timestamps where a speaker changes.

Data tagging is the loosest term, often meaning attaching keywords or attributes, sometimes several per item, for search and organization as much as for model training.

Vendors and job listings use all three interchangeably, so don't read too much into which word a company picked.

When the difference actually matters

It matters when you scope work or buy tools:

• Item-level labels are fast and cheap, and models can often do a first pass. A closed question per item fits naturally.
• Span and region annotation needs specialized interfaces and more human time per item.
• Multi-attribute tagging is really several labels per item, which is how multi-label classification treats it.

Getting the type right up front sets the budget. Asking for "annotation" when you need item labels can triple a quote.

Where decision models fit

Jev (what Jev is) answers closed questions about text with a probability per answer, which makes it a fit for item-level labeling and tagging: one question per label or tag. It generates no text and doesn't mark spans, so region and span annotation stay with other tools. The model-first labeling method is on the AI data labeling page.

Frequently asked questions

Is data annotation the same as data labeling?

Mostly. When distinguished, labeling assigns a category to a whole item and annotation marks up parts of an item.

What is data tagging?

Attaching keywords or attributes to items, often several per item. It overlaps heavily with labeling.

Which term should I use when hiring or buying?

Describe the actual task instead: item labels, span markup, or bounding boxes. The label on the task matters less than the spec.

Can AI do data annotation?

For item-level labels on text, a model first pass works well with human review. Span and image annotation need specialized tools. Compare options in data labeling services vs DIY.