Paladin: an annotation tool based on active and proactive learning
Minh-Quoc Nghiem, Paul Baylis, Sophia Ananiadou
Abstract
In this paper, we present Paladin, an opensource web-based annotation tool for creating high-quality multi-label document-level datasets. By integrating active learning and proactive learning to the annotation task, Paladin makes the task less time-consuming and requiring less human effort. Although Paladin is designed for multi-label settings, the system is flexible and can be adapted to other tasks in single-label settings.
Topics & Concepts
AnnotationTask (project management)Computer scienceArtificial intelligenceQuality (philosophy)Active learning (machine learning)EngineeringSystems engineeringPhilosophyEpistemologyMachine Learning and AlgorithmsNatural Language Processing TechniquesTopic Modeling