Abstract
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.- Anthology ID:
- 2021.eacl-demos.28
- Volume:
- Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
- Month:
- April
- Year:
- 2021
- Address:
- Online
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 238–243
- Language:
- URL:
- https://aclanthology.org/2021.eacl-demos.28
- DOI:
- 10.18653/v1/2021.eacl-demos.28
- Cite (ACL):
- Minh-Quoc Nghiem, Paul Baylis, and Sophia Ananiadou. 2021. Paladin: an annotation tool based on active and proactive learning. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 238–243, Online. Association for Computational Linguistics.
- Cite (Informal):
- Paladin: an annotation tool based on active and proactive learning (Nghiem et al., EACL 2021)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2021.eacl-demos.28.pdf