Supervised Relation Extraction

Supervised Relation Extraction is a relation extraction paradigm that operates under the assumption of having access to manually annotated training data, where the relations between entities are explicitly labeled, enabling the induction of a predictive model through supervised learning techniques.

84

Publications

9.8K

Citations

299

Authors

109

Institutions

Publications per year

2017–2026

54

Authors

299

  1. RG
    Ralph Grishman

    New York University, United States

    5 publications · 403 citations

    5

    h-index

  2. CD
    Christopher D. Manning

    Stanford University, United States

    3 publications · 1K citations

    3

    h-index

  3. YZ
    Yueting Zhuang

    Zhejiang University, China

    2 publications · 76 citations

    2

    h-index

  4. MS
    Maosong Sun

    Tsinghua University, China

    2 publications · 94 citations

    2

    h-index

  5. TP
    Tao Peng

    Jilin University, China

    2 publications · 43 citations

    2

    h-index

1–5 of 299

Venues

  1. Knowledge-Based Systems

    4 publications · 104 citations

    5

    h-index

  2. arXiv (Cornell University)

    Repository · 4 publications · 198 citations

    5

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 90 citations

    3

    h-index

  4. Neural Networks

    3 publications · 58 citations

    3

    h-index

  5. PLoS ONE

    2 publications · 181 citations

    2

    h-index

1–5