@inproceedings{zhang-etal-2023-human,
title = "Human-in-the-loop Schema Induction",
author = "Zhang, Tianyi and
Tham, Isaac and
Hou, Zhaoyi and
Ren, Jiaxuan and
Zhou, Leon and
Xu, Hainiu and
Zhang, Li and
Martin, Lara and
Dror, Rotem and
Li, Sha and
Ji, Heng and
Palmer, Martha and
Brown, Susan Windisch and
Suchocki, Reece and
Callison-Burch, Chris",
editor = "Bollegala, Danushka and
Huang, Ruihong and
Ritter, Alan",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-demo.1",
doi = "10.18653/v1/2023.acl-demo.1",
pages = "1--10",
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. 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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<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. 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.</abstract>
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%0 Conference Proceedings
%T Human-in-the-loop Schema Induction
%A Zhang, Tianyi
%A Tham, Isaac
%A Hou, Zhaoyi
%A Ren, Jiaxuan
%A Zhou, Leon
%A Xu, Hainiu
%A Zhang, Li
%A Martin, Lara
%A Dror, Rotem
%A Li, Sha
%A Ji, Heng
%A Palmer, Martha
%A Brown, Susan Windisch
%A Suchocki, Reece
%A Callison-Burch, Chris
%Y Bollegala, Danushka
%Y Huang, Ruihong
%Y Ritter, Alan
%S Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F zhang-etal-2023-human
%X 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. 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.
%R 10.18653/v1/2023.acl-demo.1
%U https://aclanthology.org/2023.acl-demo.1
%U https://doi.org/10.18653/v1/2023.acl-demo.1
%P 1-10
Markdown (Informal)
[Human-in-the-loop Schema Induction](https://aclanthology.org/2023.acl-demo.1) (Zhang et al., ACL 2023)
ACL
- Tianyi Zhang, Isaac Tham, Zhaoyi Hou, Jiaxuan Ren, Leon Zhou, Hainiu Xu, Li Zhang, Lara Martin, Rotem Dror, Sha Li, Heng Ji, Martha Palmer, Susan Windisch Brown, Reece Suchocki, and Chris Callison-Burch. 2023. Human-in-the-loop Schema Induction. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 1–10, Toronto, Canada. Association for Computational Linguistics.