@inproceedings{dror-etal-2023-zero,
title = "Zero-Shot On-the-Fly Event Schema Induction",
author = "Dror, Rotem and
Wang, Haoyu and
Roth, Dan",
editor = "Vlachos, Andreas and
Augenstein, Isabelle",
booktitle = "Findings of the Association for Computational Linguistics: EACL 2023",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-eacl.53",
doi = "10.18653/v1/2023.findings-eacl.53",
pages = "705--725",
abstract = "What are the events involved in a pandemic outbreak? What steps should be taken when planning a wedding? The answers to these questions can be found by collecting many documents on the complex event of interest, extracting relevant information, and analyzing it. We present a new approach in which large language models are utilized to generate source documents that allow predicting, given a high-level event definition, the specific events, arguments, and relations between them to construct a schema that describes the complex event in its entirety. Using our model, complete schemas on any topic can be generated on-the-fly without any manual data collection, i.e., in a zero-shot manner. Moreover, we develop efficient methods to extract pertinent information from texts and demonstrate in a series of experiments that these schemas are considered to be more complete than human-curated ones in the majority of examined scenarios. Finally, we show that this framework is comparable in performance with previous supervised schema induction methods that rely on collecting real texts and even reaching the best score in the prediction task.",
}
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%0 Conference Proceedings
%T Zero-Shot On-the-Fly Event Schema Induction
%A Dror, Rotem
%A Wang, Haoyu
%A Roth, Dan
%Y Vlachos, Andreas
%Y Augenstein, Isabelle
%S Findings of the Association for Computational Linguistics: EACL 2023
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F dror-etal-2023-zero
%X What are the events involved in a pandemic outbreak? What steps should be taken when planning a wedding? The answers to these questions can be found by collecting many documents on the complex event of interest, extracting relevant information, and analyzing it. We present a new approach in which large language models are utilized to generate source documents that allow predicting, given a high-level event definition, the specific events, arguments, and relations between them to construct a schema that describes the complex event in its entirety. Using our model, complete schemas on any topic can be generated on-the-fly without any manual data collection, i.e., in a zero-shot manner. Moreover, we develop efficient methods to extract pertinent information from texts and demonstrate in a series of experiments that these schemas are considered to be more complete than human-curated ones in the majority of examined scenarios. Finally, we show that this framework is comparable in performance with previous supervised schema induction methods that rely on collecting real texts and even reaching the best score in the prediction task.
%R 10.18653/v1/2023.findings-eacl.53
%U https://aclanthology.org/2023.findings-eacl.53
%U https://doi.org/10.18653/v1/2023.findings-eacl.53
%P 705-725
Markdown (Informal)
[Zero-Shot On-the-Fly Event Schema Induction](https://aclanthology.org/2023.findings-eacl.53) (Dror et al., Findings 2023)
ACL
- Rotem Dror, Haoyu Wang, and Dan Roth. 2023. Zero-Shot On-the-Fly Event Schema Induction. In Findings of the Association for Computational Linguistics: EACL 2023, pages 705–725, Dubrovnik, Croatia. Association for Computational Linguistics.