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.
CITATION STYLE
Nghiem, M. Q., Baylis, P., & Ananiadou, S. (2021). Paladin: An annotation tool based on active and proactive learning. In EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the System Demonstrations (pp. 238–243). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.eacl-demos.28
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