Human-in-the-Loop Schema Induction
February 25, 2023 Β· Declared Dead Β· π Annual Meeting of the Association for Computational Linguistics
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Authors
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
arXiv ID
2302.13048
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CL
Citations
22
Venue
Annual Meeting of the Association for Computational Linguistics
Last Checked
3 months ago
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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