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

Authors

392

  1. NZ
    Ningyu Zhang

    Zhejiang University, China

    8 publications · 518 citations

    8

    h-index

  2. SD
    Shumin Deng

    Zhejiang University, China

    6 publications · 268 citations

    6

    h-index

  3. HC
    Huajun Chen

    Zhejiang University, China

    5 publications · 243 citations

    5

    h-index

  4. HY
    Hongbin Ye

    Zhejiang University, China

    5 publications · 252 citations

    5

    h-index

  5. MG
    Marko Grobelnik

    Jožef Stefan Institute, Slovenia

    3 publications · 163 citations

    3

    h-index

1–5 of 392

Venues

  1. arXiv (Cornell University)

    Repository · 10 publications · 199 citations

    10

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  2. Applied Sciences

    3 publications · 98 citations

    4

    h-index

  3. Neurocomputing

    1 publications · 46 citations

    3

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 33 citations

    3

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 371 citations

    3

    h-index

1–5