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A multi-label multi-hop relation detection model based on relation-aware sequence generation
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Zhang, Linhai, Zhou, Deyu, Lin, Chao and He, Yulan (2021) A multi-label multi-hop relation detection model based on relation-aware sequence generation. In: 2021 Conference on Empirical Methods in Natural Language Processing, Punta Cana, Dominican Republic, 7-11 Nov 2021. Published in: Findings of the Association for Computational Linguistics: EMNLP 2021 pp. 4713-4719. doi:10.18653/v1/2021.findings-emnlp.404
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Official URL: http://dx.doi.org/10.18653/v1/2021.findings-emnlp....
Abstract
Multi-hop relation detection in Knowledge Base Question Answering (KBQA) aims at retrieving the relation path starting from the topic entity to the answer node based on a given question, where the relation path may comprise multiple relations. Most of the existing methods treat it as a single-label learning problem while ignoring the fact that for some complex questions, there exist multiple correct relation paths in knowledge bases. Therefore, in this paper, multi-hop relation detection is considered as a multi-label learning problem. However, performing multi-label multi-hop relation detection is challenging since the numbers of both the labels and the hops are unknown. To tackle this challenge, multi-label multi-hop relation detection is formulated as a sequence generation task. A relation-aware sequence relation generation model is proposed to solve the problem in an end-to-end manner. Experimental results show the effectiveness of the proposed method for relation detection and KBQA.
Item Type: | Conference Item (Paper) | |||||||||||||||
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Subjects: | P Language and Literature > P Philology. Linguistics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | |||||||||||||||
Library of Congress Subject Headings (LCSH): | Neural networks (Computer science), Natural language processing (Computer science), Computational linguistics , Pattern recognition systems, Querying (Computer science) | |||||||||||||||
Journal or Publication Title: | Findings of the Association for Computational Linguistics: EMNLP 2021 | |||||||||||||||
Publisher: | ACL | |||||||||||||||
Book Title: | Findings of the Association for Computational Linguistics: EMNLP 2021 | |||||||||||||||
Official Date: | 2021 | |||||||||||||||
Dates: |
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Page Range: | pp. 4713-4719 | |||||||||||||||
DOI: | 10.18653/v1/2021.findings-emnlp.404 | |||||||||||||||
Status: | Peer Reviewed | |||||||||||||||
Publication Status: | Published | |||||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | |||||||||||||||
Copyright Holders: | Association for Computational Linguistics | |||||||||||||||
Date of first compliant deposit: | 31 May 2022 | |||||||||||||||
Date of first compliant Open Access: | 1 June 2022 | |||||||||||||||
RIOXX Funder/Project Grant: |
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Conference Paper Type: | Paper | |||||||||||||||
Title of Event: | 2021 Conference on Empirical Methods in Natural Language Processing | |||||||||||||||
Type of Event: | Conference | |||||||||||||||
Location of Event: | Punta Cana, Dominican Republic | |||||||||||||||
Date(s) of Event: | 7-11 Nov 2021 | |||||||||||||||
Related URLs: |
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