Constructing Procedural Graphs with Multiple Dependency Relations: A New Dataset and Baseline

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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.

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Ren, H., Zeng, Y., Cai, Y., Zhou, B., & Lian, Z. (2023). Constructing Procedural Graphs with Multiple Dependency Relations: A New Dataset and Baseline. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 8474–8486). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.findings-acl.536

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