Triple Extraction
Triple Extraction is a computational process within knowledge graph construction that identifies and structurally formalizes subject-predicate-object triples from unstructured or semi-structured text, distinguishing itself by enabling the explicit representation of factual assertions in machine-readable form.
123
Publications
5.6K
Citations
392
Authors
159
Institutions
Publications per year
2017–2026
82
Parents
123
A Novel Cascade Binary Tagging Framework for Relational Triple Extraction
Zhepei Wei, Jianlin Su, Yue Wang et al. · 2020 · 622 citations · Full text
Position-Aware Tagging for Aspect Sentiment Triplet Extraction
Lu Xu, Hao Li, Wei Lu et al. · 2020 · 265 citations · Full text
PRGC: Potential Relation and Global Correspondence Based Joint Relational Triple Extraction
Hengyi Zheng, Rui Wen, Xi Chen et al. · 2021 · 238 citations · Full text
From data fusion to knowledge fusion
Xin Luna Dong, Evgeniy Gabrilovich, Geremy Heitz et al. · Proceedings of the VLDB Endowment · 2014 · 232 citations
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159

Zhejiang University
Hangzhou, China
9 h-index
28 publications
1.4K citations

Chinese Academy of Sciences
Beijing, China
5 h-index
9 publications
1.2K citations

Northeastern University
Shenyang, China
5 h-index
23 publications
1.2K citations
Alibaba Group (United States)
San Mateo, United States
5 h-index
12 publications
1.3K citations

Shanghai Jiao Tong University
Shanghai, China
4 h-index
7 publications
186 citations

Alibaba Group (China)
Hangzhou, China
3 h-index
9 publications
327 citations

Universidad de Sevilla
Seville, Spain
3 h-index
11 publications
229 citations
Rensselaer Polytechnic Institute
Troy, United States
3 h-index
10 publications
178 citations
1–8 of 159
Repository · 10 publications · 199 citations
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3 publications · 98 citations
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1 publications · 46 citations
3
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TKDE · 2 publications · 33 citations
3
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Conference · 3 publications · 371 citations
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