Super.AI

Documentation

Welcome to super.AI. We provide AI and human data labeling.

Output data types

Super.AI provides an ever-growing selection of output data types. Below you can find a list of our currently available data types, along with a brief description and an example project type for each. If you don’t see the output type that you’re interested in, reach out to us as we can probably work something out.

A super.AI project type will take a certain input data type and produce a specific output data type. Some projects take more than one input data type and/or use more than one output data type.

Data type

Description

Example project type

Text

Text metadata is added to the input data

Image captioning

Number

Numerical metadata is added to the input data. This can be a float value, e.g., 2.3.

Image similarity

Integer

Numerical metadata is added to the input data. This can only be a whole number, e.g., 3.

Image counting

Bounding box

A 2D box is drawn over objects of interest in an image or video.

Image bounding box

Binary choice

Either true or false. Only one option can be selected.

Product feature verification

Exclusive choice

The most appropriate option is selected from a list. Only one option can be selected—just like with a radio-button list.

Image categorization

Multiple choice

The most appropriate options are selected from a list. Multiple options can be selected—just like with a checkbox list.

Image tagging

Text annotation

Metadata is added to text content. For example, labeling nouns or company names.

Named entity recognition

Object

A combination of different labeling methods are used to produce a single label. For example, a collection of text transcription fields.

URL transcription

Updated about a month ago


Output data types


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