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Definitions

Annotation

The metadata created from the labeling work on assets. For example, a box delimiting the house on the satellite image, or the selection of textual information related to its typology of named entities.

Multiple annotations can be added on a given asset, to create a label.

Annotating

The action of creating metadata to characterize an asset and make it fit for training machine learning models. For example, identifying a house on a satellite image, or attaching textual information to a type of named entity on a document. Also called labeling.

Asset

A file/document. This could be a photograph, a satellite image, a video, a PDF, an email, etc.

Consensus

A quality parameter to measure the agreement between several annotations made on the same asset by different labelers. Ensures consistency between annotators and helps achieve top data quality for your project.

Dataset

A collection of assets to be annotated.

Honeypot

A quality parameter to measure the agreement between a pre-annotated asset (gold standard) and the annotations made by labelers.

Instructions

Instructions are guidance available in the annotation interface to help labelers complete their tasks. They can be defined at the project and job levels.

Interface

The graphical user interface configured at the beginning of a project and made available to users to enable them to perform the annotation tasks.

Job

Labeling (or annotation) jobs are labeling tasks which are associated with specific tools or input types.
For example, each one of these can be considered a Kili labeling job:

  • Classification task with a multi choice dropdown input type
  • Object detection task with the polygon tool
  • Named entities recognition task

Label

The combination of all annotations created on an asset. The annotations that comprise a label don’t have to be the product of one type of labeling job. For example, all houses identified on a satellite image, all annotated fragments of text in a document, or the combination of annotated named entities and a text classification in a text file would all be considered a label.

Labeling

The action of creating metadata to characterize an asset and make it fit for training machine learning models. For example, identifying a house on a satellite image, or attaching textual information to a type of named entity on a document. Also called annotating.

Organization

An organization contains users who can create projects and easily collaborate. A project belongs to an organization when its author is a member of the organization.

Project

A project is the combination of:

  • A dataset
  • An interface adapted to the annotation task that we want to perform on the dataset
  • Members with different roles (for example, labelers and reviewers)
  • Settings regarding quality management workflow