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Bureau for Rapid Annotation Tool: collaboration can do more among variance annotations

Zheng Wang (Institute of Scientific and Technical Information of China, Beijing, China)
Shuo Xu (School of Economics and Management, Beijing University of Technology, Beijing, China)
Yibo Wang (Institute of Scientific and Technical Information of China, Beijing, China)
Xiaojiao Chai (Institute of Scientific and Technical Information of China, Beijing, China)
Liang Chen (Institute of Scientific and Technical Information of China, Beijing, China)

Aslib Journal of Information Management

ISSN: 2050-3806

Article publication date: 12 September 2022

Issue publication date: 19 June 2023

102

Abstract

Purpose

The purpose of this study is to solve the problems caused by the growing volumes of pre-annotated literature and variety-oriented annotations, including teamwork, quality control and time effort.

Design/methodology/approach

An annotation collaboration workbench is developed, which is named as Bureau for Rapid Annotation Tool (Brat). Main functionalities include an enhanced semantic constraint system, Vim-like shortcut keys, an annotation filter and a graph-visualizing annotation browser. With these functionalities, the annotators are encouraged to question their initial mindset, inspect conflicts and gain agreement from their peers.

Findings

The collaborative patterns can indeed be leveraged to structure properly every annotator’s behaviors. The Brat workbench can actually be seen as an experienced-based annotation tool by harnessing collective intelligence. Compared to previous counterparts, about one-third of time can be saved on Xinhuanet military news and patent corpora with the workbench.

Originality/value

The various annotations are very popular in real-world annotation tasks with multiple annotators. Though, it is still under-discussed on variety-oriented annotations. The findings of this study provide the practitioners valuable insight into how to govern annotation projects. In addition, the Brat workbench takes the first step for future research on annotating large-scale text resources.

Keywords

Acknowledgements

The present study is an extended version of an article (Wang and Xu, 2021) presented at the second Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents at the JCDL 2021, 30 September, 2021. This work is supported partially by the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDA16040504), National Key Research and Development Program of China (Grant No. 2019YFA0707202), and National Natural Science Foundation of China (Grant No. 72074014 and 71704169). The authors also thank Professor Yiming Jing and Rui Zheng for their assistance on how to understand the collaboration in the field of psychology.

Citation

Wang, Z., Xu, S., Wang, Y., Chai, X. and Chen, L. (2023), "Bureau for Rapid Annotation Tool: collaboration can do more among variance annotations", Aslib Journal of Information Management, Vol. 75 No. 3, pp. 523-534. https://doi.org/10.1108/AJIM-01-2022-0046

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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