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Models/TransE

TransE

Reported on 37 benchmarks across 2 tasks · 3 papers · 1 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Graphs37 results

  • Link PredictiononWikidata5M
    Hits@10· 2019-11-13
    0.392
    best: 0.591 (MoCoKGC)
    SOTA
    KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language RepresentationarXiv:1911.06136
  • Link PredictiononICEWS05-15
    MRR· 2022-03-15
    0.294
    best: 0.713 (SPA)
    RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph CompletionarXiv:2203.07993
  • Link PredictiononGDELT
    MRR· 2022-03-15
    0.113
    best: 0.36 (SPA)
    RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph CompletionarXiv:2203.07993
  • Link PredictiononICEWS14
    MRR· 2022-03-15
    0.28
    best: 0.658 (SPA)
    RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph CompletionarXiv:2203.07993
  • Link PredictiononCoDEx Small
    Hits@1· 2020-09-16
    0.339
    best: 0.375 (ComplEx-N3-RP)
    CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkarXiv:2009.07810
  • Link PredictiononCoDEx Small
    Hits@10· 2020-09-16
    0.638
    best: 0.663 (ComplEx-N3-RP)
    CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkarXiv:2009.07810
  • Link PredictiononCoDEx Small
    Hits@3· 2020-09-16
    0.4975
    best: 0.514 (ComplEx-N3-RP)
    CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkarXiv:2009.07810
  • Link PredictiononCoDEx Small
    MRR· 2020-09-16
    0.354
    best: 0.473 (ComplEx-N3-RP)
    CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkarXiv:2009.07810
  • Link PredictiononCoDEx Medium
    Hits@1· 2020-09-16
    0.259
    best: 0.277 (ComplEx-N3-RP)
    CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkarXiv:2009.07810
  • Link PredictiononCoDEx Medium
    Hits@10· 2020-09-16
    0.458
    best: 0.525 (ULTRA)
    CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkarXiv:2009.07810
  • Link PredictiononCoDEx Medium
    Hits@3· 2020-09-16
    0.3599
    best: 0.386 (ComplEx-N3-RP)
    CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkarXiv:2009.07810
  • Link PredictiononCoDEx Medium
    MRR· 2020-09-16
    0.303
    best: 0.372 (ULTRA)
    CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkarXiv:2009.07810
  • Link PredictiononCoDEx Large
    Hits@1· 2020-09-16
    0.116
    best: 0.277 (ComplEx-N3-RP)
    CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkarXiv:2009.07810
  • Link PredictiononCoDEx Large
    Hits@10· 2020-09-16
    0.317
    best: 0.473 (ComplEx-N3-RP)
    CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkarXiv:2009.07810
  • Link PredictiononCoDEx Large
    Hits@3· 2020-09-16
    0.2188
    best: 0.377 (ComplEx-N3-RP)
    CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkarXiv:2009.07810
  • Link PredictiononCoDEx Large
    MRR· 2020-09-16
    0.187
    best: 0.345 (ComplEx-N3-RP)
    CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkarXiv:2009.07810
  • Link PredictiononWikidata5M
    Hits@1· 2019-11-13
    0.17
    best: 0.435 (MoCoKGC)
    KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language RepresentationarXiv:1911.06136
  • Link PredictiononWikidata5M
    Hits@3· 2019-11-13
    0.311
    best: 0.517 (MoCoKGC)
    KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language RepresentationarXiv:1911.06136
  • Link PredictiononWikidata5M
    MRR· 2019-11-13
    0.253
    best: 0.49 (MoCoKGC)
    KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language RepresentationarXiv:1911.06136
  • Link Predictionon FB15k
    Hits@10
    0.471
    best: 0.914 (AutoKGE)
  • Link Predictionon FB15k
    MR
    125
    best: 2501 (Inverse Model)
  • Link PredictiononUMLS
    Hits@10
    0.989
    best: 1 (LP-BERT)
  • Link PredictiononUMLS
    MR
    1.84
    best: 5.52 (DistMult)
  • Link PredictiononFB122
    HITS@3
    58.9
    best: 74.2 (Prob-CBR)
  • Link PredictiononFB122
    Hits@10
    70.2
    best: 78.2 (Prob-CBR)
  • Link PredictiononFB122
    Hits@5
    64.2
    best: 76 (Prob-CBR)
  • Link PredictiononFB122
    MRR
    48
    best: 72.7 (Prob-CBR)
  • Link PredictiononWN18RR
    Hits@1
    0.4226
    best: 0.665 (MoCoKGC)
  • Link PredictiononWN18RR
    Hits@10
    0.5555
    best: 0.881 (MoCoKGC)
  • Link PredictiononWN18RR
    MRR
    0.4659
    best: 0.742 (MoCoKGC)
  • Link PredictiononWN18
    Hits@10
    0.754
    best: 0.964 (Inverse Model)
  • Link PredictiononWN18
    MR
    263
    best: 1072 (ComplEx NSCaching)
  • Link PredictiononFB15k-237
    Hits@1
    0.1987
    best: 0.321 (NBFNet)
  • Link PredictiononFB15k-237
    Hits@10
    0.4709
    best: 0.599 (NBFNet)
  • Link PredictiononFB15k-237
    MRR
    0.2904
    best: 0.415 (NBFNet)
  • Link PredictiononOpenBioLink
    Hits@10
    0.446
    best: 0.542 (DistMult)
  • Link Property Predictiononogbl-biokg
    Number of params
    187648000
    best: 849427106 (RelEns)