Paul Baylis


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Paladin: an annotation tool based on active and proactive learning
Minh-Quoc Nghiem | Paul Baylis | Sophia Ananiadou
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations

In this paper, we present Paladin, an open-source 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.