App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 7

Iterative open information extraction based on biaffine attention

Li Xin1,2
Shao Jingqi1,2
Wang Hao1,2
He Li1,2
Duan Jianyong1,2
1. School of Information Science & Technology, North China University of Technology, Beijing 100144, China
2. CNONIX National Standard Application & Promotion Lab, Beijing 100144, China
DOI: 10.19734/j.issn.1001-3695.2023.10.0543

Abstract

The current Open Information Extraction (OpenIE) methods cannot take into account the compactness of the extraction results and the performance of the model at the same time, which makes the extraction results cannot be better applied to downstream tasks. Therefore, this paper proposes a model that uses Biaffine Attention for table filling and iterative extraction. First, the model learns the directional information between words through Biaffine Attention, captures the interaction between word pairs, and then fills the two-dimensional table to make the components in the sentence share each other and identify compact components; Secondly, the Multi-Head Attention mechanism is used to apply the representation of predicates and parameters to the context embedding, making the extraction of predicates and parameters dependent on each other and better linking the relationship components and parameter components; Finally, for sentences containing multiple relational components, iterative extraction is used to capture the inherent dependencies between each extraction without recoding. Experiments on the public datasets CaRB and Wire57 show that this method achieves higher precision and recall than baseline methods, improving F1 values by at least 1.4% and 3.2%, while producing shorter and more semantically rich extractions.

Foundation Support

国家重点研发计划资助项目(2020AAA0109700)
国家自然科学基金资助项目(62076167、61972003)
北京市教委研发计划(KM202210009002)
北方工业大学北京城市治理研究基地(2023CSZL16)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.10.0543
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 7

Publish History

[2024-01-23] Accepted Paper

Cite This Article

李欣, 邵靖淇, 王昊, 等. 基于双仿射注意力的迭代式开放域信息抽取 [J]. 计算机应用研究, 2024, 41 (7). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.10.0543. (Li Xin, Shao Jingqi, Wang Hao, et al. Iterative open information extraction based on biaffine attention [J]. Application Research of Computers, 2024, 41 (7). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.10.0543. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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