Human-in-The-loop schema induction

Tianyi Zhang; Isaac Tham; Zhaoyi Hou; Jiaxuan Ren; Liyang Zhou; Hainiu Xu; Li Zhang; Lara J. Martin; Rotem Dror; Sha Li; Heng Ji; Martha Palmer; Susan Brown; Reece Suchocki; Chris Callison-Burch

Human-in-The-loop schema induction

Tianyi Zhang, Isaac Tham, Zhaoyi Hou, Jiaxuan Ren, Liyang Zhou, Hainiu Xu, Li Zhang, Lara J. Martin, Rotem Dror, Sha Li, Heng Ji, Martha Palmer, Susan Brown, Reece Suchocki, Chris Callison-Burch

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Schema induction builds a graph representation explaining how events unfold in a scenario. Existing approaches have been based on information retrieval (IR) and information extraction (IE), often with limited human curation. We demonstrate a human-in-The-loop schema induction system powered by GPT-3.1 We first describe the different modules of our system, including prompting to generate schematic elements, manual edit of those elements, and conversion of those into a schema graph. By qualitatively comparing our system to previous ones, we show that our system not only transfers to new domains more easily than previous approaches but also reduces efforts of human curation thanks to our interactive interface.

Original language	English
Title of host publication	System Demonstrations
Publisher	Association for Computational Linguistics (ACL)
Pages	1-10
Number of pages	10
ISBN (Electronic)	9781959429708
State	Published - 2023
Externally published	Yes
Event	61st Annual Meeting of the Association for Computational Linguistics, ACL-DEMO 2023 - Toronto, Canada Duration: 10 Jul 2023 → 12 Jul 2023

Publication series

Name	Proceedings of the Annual Meeting of the Association for Computational Linguistics
Volume	3
ISSN (Print)	0736-587X

Conference

Conference	61st Annual Meeting of the Association for Computational Linguistics, ACL-DEMO 2023
Country/Territory	Canada
City	Toronto
Period	10/07/23 → 12/07/23

Bibliographical note

Publisher Copyright:
© ACL-DEMO 2023. All rights reserved.

ASJC Scopus subject areas

Computer Science Applications
Linguistics and Language
Language and Linguistics

Cite this

Zhang, T., Tham, I., Hou, Z., Ren, J., Zhou, L., Xu, H., Zhang, L., Martin, L. J., Dror, R., Li, S., Ji, H., Palmer, M., Brown, S., Suchocki, R., & Callison-Burch, C. (2023). Human-in-The-loop schema induction. In System Demonstrations (pp. 1-10). (Proceedings of the Annual Meeting of the Association for Computational Linguistics; Vol. 3). Association for Computational Linguistics (ACL).

@inproceedings{8929ea14b0e542f7babdb0130f002ee4,

title = "Human-in-The-loop schema induction",

abstract = "Schema induction builds a graph representation explaining how events unfold in a scenario. Existing approaches have been based on information retrieval (IR) and information extraction (IE), often with limited human curation. We demonstrate a human-in-The-loop schema induction system powered by GPT-3.1 We first describe the different modules of our system, including prompting to generate schematic elements, manual edit of those elements, and conversion of those into a schema graph. By qualitatively comparing our system to previous ones, we show that our system not only transfers to new domains more easily than previous approaches but also reduces efforts of human curation thanks to our interactive interface.",

author = "Tianyi Zhang and Isaac Tham and Zhaoyi Hou and Jiaxuan Ren and Liyang Zhou and Hainiu Xu and Li Zhang and Martin, {Lara J.} and Rotem Dror and Sha Li and Heng Ji and Martha Palmer and Susan Brown and Reece Suchocki and Chris Callison-Burch",

note = "Publisher Copyright: {\textcopyright} ACL-DEMO 2023. All rights reserved.; 61st Annual Meeting of the Association for Computational Linguistics, ACL-DEMO 2023 ; Conference date: 10-07-2023 Through 12-07-2023",

year = "2023",

language = "English",

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

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

pages = "1--10",

booktitle = "System Demonstrations",

address = "United States",

}

Zhang, T, Tham, I, Hou, Z, Ren, J, Zhou, L, Xu, H, Zhang, L, Martin, LJ, Dror, R, Li, S, Ji, H, Palmer, M, Brown, S, Suchocki, R & Callison-Burch, C 2023, Human-in-The-loop schema induction. in System Demonstrations. Proceedings of the Annual Meeting of the Association for Computational Linguistics, vol. 3, Association for Computational Linguistics (ACL), pp. 1-10, 61st Annual Meeting of the Association for Computational Linguistics, ACL-DEMO 2023, Toronto, Canada, 10/07/23.

TY - GEN

T1 - Human-in-The-loop schema induction

AU - Zhang, Tianyi

AU - Tham, Isaac

AU - Hou, Zhaoyi

AU - Ren, Jiaxuan

AU - Zhou, Liyang

AU - Xu, Hainiu

AU - Zhang, Li

AU - Martin, Lara J.

AU - Dror, Rotem

AU - Li, Sha

AU - Ji, Heng

AU - Palmer, Martha

AU - Brown, Susan

AU - Suchocki, Reece

AU - Callison-Burch, Chris

PY - 2023

Y1 - 2023

N2 - Schema induction builds a graph representation explaining how events unfold in a scenario. Existing approaches have been based on information retrieval (IR) and information extraction (IE), often with limited human curation. We demonstrate a human-in-The-loop schema induction system powered by GPT-3.1 We first describe the different modules of our system, including prompting to generate schematic elements, manual edit of those elements, and conversion of those into a schema graph. By qualitatively comparing our system to previous ones, we show that our system not only transfers to new domains more easily than previous approaches but also reduces efforts of human curation thanks to our interactive interface.

AB - Schema induction builds a graph representation explaining how events unfold in a scenario. Existing approaches have been based on information retrieval (IR) and information extraction (IE), often with limited human curation. We demonstrate a human-in-The-loop schema induction system powered by GPT-3.1 We first describe the different modules of our system, including prompting to generate schematic elements, manual edit of those elements, and conversion of those into a schema graph. By qualitatively comparing our system to previous ones, we show that our system not only transfers to new domains more easily than previous approaches but also reduces efforts of human curation thanks to our interactive interface.

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M3 - Conference contribution

AN - SCOPUS:85162730782

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

SP - 1

EP - 10

BT - System Demonstrations

PB - Association for Computational Linguistics (ACL)

T2 - 61st Annual Meeting of the Association for Computational Linguistics, ACL-DEMO 2023

Y2 - 10 July 2023 through 12 July 2023

ER -

Human-in-The-loop schema induction

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

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Cite this