QuickGraph: A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text

Tyler Bikaun; Michael Stewart; Wei Liu

doi:10.18653/v1/2022.acl-demo.27

QuickGraph: A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text

Tyler Bikaun, Michael Stewart, Wei Liu

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

11 Citations (Scopus)

Abstract

Acquiring high-quality annotated corpora for complex multi-task information extraction (MT-IE) is an arduous and costly process for human-annotators. Adoption of unsupervised techniques for automated annotation have thus become popular. However, these techniques rely heavily on dictionaries, gazetteers, and knowledge bases. While such resources are abundant for general domains, they are scarce for specialised technical domains. To tackle this challenge, we present QuickGraph(1), the first collaborative MT-IE annotation tool built with indirect weak supervision and clustering to maximise annotator productivity.

QuickGraph's main contribution is a set of novel features that enable knowledge graph extraction through rapid and consistent complex multi-task entity and relation annotation. In this paper, we discuss these key features and qualitatively compare QuickGraph to existing annotation tools. A demonstration of our system is available at: https://youtu.be/ ZlzH-AAoGXs.

Original language	English
Title of host publication	Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
Editors	Valerio Basile, Zornitsa Kozareva, Sanja Stajner
Place of Publication	USA
Publisher	Association for Computational Linguistics (ACL)
Pages	270-278
Number of pages	9
ISBN (Electronic)	978-1-955917-24-7
DOIs	https://doi.org/10.18653/v1/2022.acl-demo.27
Publication status	Published - 2022
Event	60th Annual Meeting of the Association-for-Computational-Linguistics (ACL) - Dublin, Ireland Duration: 22 May 2022 → 27 May 2022

Publication series

Name	Proceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)	0736-587X

Conference

Conference	60th Annual Meeting of the Association-for-Computational-Linguistics (ACL)
Country/Territory	Ireland
City	Dublin
Period	22/05/22 → 27/05/22

Access to Document

10.18653/v1/2022.acl-demo.27Licence: CC BY

1 Curtailed
1 Finished

ARC Training Centre for Transforming Maintenance through Data Science
Rohl, A. (Investigator 01), Small, M. (Investigator 02), Hodkiewicz, M. (Investigator 03), Loxton, R. (Investigator 04), O'Halloran, K. (Investigator 05), Tan, T. (Investigator 06), Calo, V. (Investigator 07), Reynolds, M. (Investigator 08), Liu, W. (Investigator 09), While, R. (Investigator 10), French, T. (Investigator 11), Cripps, E. (Investigator 12), Cardell-Oliver, R. (Investigator 13) & Correa, D. (Investigator 14)
ARC Australian Research Council
1/01/19 → 24/02/25
Project: Research
A Cross-National and Cross-Cultural Study of Global Translation Industry
Ji, M. (Investigator 01), Togneri, R. (Investigator 02), Liu, W. (Investigator 03), De Sutter, G. (Investigator 04), Diaz Cintas, J. (Investigator 05), Laviosa, S. (Investigator 06), Pagano, A. (Investigator 07) & Wright, S.-E. (Investigator 08)
ARC Australian Research Council
1/01/15 → 30/12/17
Project: Research

Cite this

Bikaun, T., Stewart, M., & Liu, W. (2022). QuickGraph: A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text. In V. Basile, Z. Kozareva, & S. Stajner (Eds.), Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations (pp. 270-278). (Proceedings of the Annual Meeting of the Association for Computational Linguistics). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.acl-demo.27

Bikaun, Tyler ; Stewart, Michael ; Liu, Wei. / QuickGraph : A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations. editor / Valerio Basile ; Zornitsa Kozareva ; Sanja Stajner. USA : Association for Computational Linguistics (ACL), 2022. pp. 270-278 (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

@inproceedings{55956fcf1f2b412c8f56e66bbb885f48,

title = "QuickGraph: A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text",

abstract = "Acquiring high-quality annotated corpora for complex multi-task information extraction (MT-IE) is an arduous and costly process for human-annotators. Adoption of unsupervised techniques for automated annotation have thus become popular. However, these techniques rely heavily on dictionaries, gazetteers, and knowledge bases. While such resources are abundant for general domains, they are scarce for specialised technical domains. To tackle this challenge, we present QuickGraph(1), the first collaborative MT-IE annotation tool built with indirect weak supervision and clustering to maximise annotator productivity.QuickGraph's main contribution is a set of novel features that enable knowledge graph extraction through rapid and consistent complex multi-task entity and relation annotation. In this paper, we discuss these key features and qualitatively compare QuickGraph to existing annotation tools. A demonstration of our system is available at: https://youtu.be/ ZlzH-AAoGXs.",

author = "Tyler Bikaun and Michael Stewart and Wei Liu",

year = "2022",

doi = "10.18653/v1/2022.acl-demo.27",

language = "English",

series = "Proceedings of the Annual Meeting of the Association for Computational Linguistics",

publisher = "Association for Computational Linguistics (ACL)",

pages = "270--278",

editor = "Valerio Basile and Zornitsa Kozareva and Sanja Stajner",

booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations",

note = "60th Annual Meeting of the Association-for-Computational-Linguistics (ACL) ; Conference date: 22-05-2022 Through 27-05-2022",

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Bikaun, T , Stewart, M & Liu, W 2022, QuickGraph: A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text. in V Basile, Z Kozareva & S Stajner (eds), Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations. Proceedings of the Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics (ACL), USA, pp. 270-278, 60th Annual Meeting of the Association-for-Computational-Linguistics (ACL), Dublin, Ireland, 22/05/22. https://doi.org/10.18653/v1/2022.acl-demo.27

QuickGraph: A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text. / Bikaun, Tyler ; Stewart, Michael ; Liu, Wei.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations. ed. / Valerio Basile; Zornitsa Kozareva; Sanja Stajner. USA: Association for Computational Linguistics (ACL), 2022. p. 270-278 (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

TY - GEN

T1 - QuickGraph

T2 - 60th Annual Meeting of the Association-for-Computational-Linguistics (ACL)

AU - Bikaun, Tyler

AU - Stewart, Michael

AU - Liu, Wei

PY - 2022

Y1 - 2022

N2 - Acquiring high-quality annotated corpora for complex multi-task information extraction (MT-IE) is an arduous and costly process for human-annotators. Adoption of unsupervised techniques for automated annotation have thus become popular. However, these techniques rely heavily on dictionaries, gazetteers, and knowledge bases. While such resources are abundant for general domains, they are scarce for specialised technical domains. To tackle this challenge, we present QuickGraph(1), the first collaborative MT-IE annotation tool built with indirect weak supervision and clustering to maximise annotator productivity.QuickGraph's main contribution is a set of novel features that enable knowledge graph extraction through rapid and consistent complex multi-task entity and relation annotation. In this paper, we discuss these key features and qualitatively compare QuickGraph to existing annotation tools. A demonstration of our system is available at: https://youtu.be/ ZlzH-AAoGXs.

AB - Acquiring high-quality annotated corpora for complex multi-task information extraction (MT-IE) is an arduous and costly process for human-annotators. Adoption of unsupervised techniques for automated annotation have thus become popular. However, these techniques rely heavily on dictionaries, gazetteers, and knowledge bases. While such resources are abundant for general domains, they are scarce for specialised technical domains. To tackle this challenge, we present QuickGraph(1), the first collaborative MT-IE annotation tool built with indirect weak supervision and clustering to maximise annotator productivity.QuickGraph's main contribution is a set of novel features that enable knowledge graph extraction through rapid and consistent complex multi-task entity and relation annotation. In this paper, we discuss these key features and qualitatively compare QuickGraph to existing annotation tools. A demonstration of our system is available at: https://youtu.be/ ZlzH-AAoGXs.

U2 - 10.18653/v1/2022.acl-demo.27

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M3 - Conference paper

T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics

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EP - 278

BT - Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

A2 - Basile, Valerio

A2 - Kozareva, Zornitsa

A2 - Stajner, Sanja

PB - Association for Computational Linguistics (ACL)

CY - USA

Y2 - 22 May 2022 through 27 May 2022

ER -

Bikaun T , Stewart M , Liu W. QuickGraph: A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text. In Basile V, Kozareva Z, Stajner S, editors, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations. USA: Association for Computational Linguistics (ACL). 2022. p. 270-278. (Proceedings of the Annual Meeting of the Association for Computational Linguistics). doi: 10.18653/v1/2022.acl-demo.27

QuickGraph: A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text

Abstract

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Projects

ARC Training Centre for Transforming Maintenance through Data Science

A Cross-National and Cross-Cultural Study of Global Translation Industry

Cite this