YEDDA: A Lightweight Collaborative Text Span Annotation Tool

Jie Yang, Yue Zhang, Linwei Li, Xingxuan Li


Abstract
In this paper, we introduce Yedda, a lightweight but efficient and comprehensive open-source tool for text span annotation. Yedda provides a systematic solution for text span annotation, ranging from collaborative user annotation to administrator evaluation and analysis. It overcomes the low efficiency of traditional text annotation tools by annotating entities through both command line and shortcut keys, which are configurable with custom labels. Yedda also gives intelligent recommendations by learning the up-to-date annotated text. An administrator client is developed to evaluate annotation quality of multiple annotators and generate detailed comparison report for each annotator pair. Experiments show that the proposed system can reduce the annotation time by half compared with existing annotation tools. And the annotation time can be further compressed by 16.47% through intelligent recommendation.
Anthology ID:
P18-4006
Volume:
Proceedings of ACL 2018, System Demonstrations
Month:
July
Year:
2018
Address:
Melbourne, Australia
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
31–36
Language:
URL:
https://www.aclweb.org/anthology/P18-4006
DOI:
10.18653/v1/P18-4006
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PDF:
http://aclanthology.lst.uni-saarland.de/P18-4006.pdf