@inproceedings{ren-etal-2023-constructing,
title = "Constructing Procedural Graphs with Multiple Dependency Relations: A New Dataset and Baseline",
author = "Ren, Haopeng and
Zeng, Yushi and
Cai, Yi and
Zhou, Bihan and
Lian, Zetao",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-acl.536",
doi = "10.18653/v1/2023.findings-acl.536",
pages = "8474--8486",
abstract = "Current structured and semi-structured knowledge bases mainly focus on representing descriptive knowledge but ignore another commonsense knowledge (Procedural Knowledge). To structure the procedural knowledge, existing methods are proposed to automatically generate flow graphs from procedural documents. They focus on extracting sequential dependency between sentences but neglect another two important dependencies (i.e., inclusion dependency and constraint dependency) in procedural documents. In our paper, we explore a problem of automatically generating procedural graph with multiple dependency relations to extend the flow graph constructed by existing methods and propose a procedural graph construction method with syntactic information and discourse structures. A new dataset (WHPG) is built and extensive experiments are conducted to evaluate the effectiveness of our proposed model.",
}
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<abstract>Current structured and semi-structured knowledge bases mainly focus on representing descriptive knowledge but ignore another commonsense knowledge (Procedural Knowledge). To structure the procedural knowledge, existing methods are proposed to automatically generate flow graphs from procedural documents. They focus on extracting sequential dependency between sentences but neglect another two important dependencies (i.e., inclusion dependency and constraint dependency) in procedural documents. In our paper, we explore a problem of automatically generating procedural graph with multiple dependency relations to extend the flow graph constructed by existing methods and propose a procedural graph construction method with syntactic information and discourse structures. A new dataset (WHPG) is built and extensive experiments are conducted to evaluate the effectiveness of our proposed model.</abstract>
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%0 Conference Proceedings
%T Constructing Procedural Graphs with Multiple Dependency Relations: A New Dataset and Baseline
%A Ren, Haopeng
%A Zeng, Yushi
%A Cai, Yi
%A Zhou, Bihan
%A Lian, Zetao
%Y Rogers, Anna
%Y Boyd-Graber, Jordan
%Y Okazaki, Naoaki
%S Findings of the Association for Computational Linguistics: ACL 2023
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F ren-etal-2023-constructing
%X Current structured and semi-structured knowledge bases mainly focus on representing descriptive knowledge but ignore another commonsense knowledge (Procedural Knowledge). To structure the procedural knowledge, existing methods are proposed to automatically generate flow graphs from procedural documents. They focus on extracting sequential dependency between sentences but neglect another two important dependencies (i.e., inclusion dependency and constraint dependency) in procedural documents. In our paper, we explore a problem of automatically generating procedural graph with multiple dependency relations to extend the flow graph constructed by existing methods and propose a procedural graph construction method with syntactic information and discourse structures. A new dataset (WHPG) is built and extensive experiments are conducted to evaluate the effectiveness of our proposed model.
%R 10.18653/v1/2023.findings-acl.536
%U https://aclanthology.org/2023.findings-acl.536
%U https://doi.org/10.18653/v1/2023.findings-acl.536
%P 8474-8486
Markdown (Informal)
[Constructing Procedural Graphs with Multiple Dependency Relations: A New Dataset and Baseline](https://aclanthology.org/2023.findings-acl.536) (Ren et al., Findings 2023)
ACL