Link prediction Predict missing heads or tails of Wikidata triples. Entities are identifiers with learned representations in the standard task; no text or image features are supplied by the core artifact. Evaluated by MRR.

Dataset details

Task

Predict missing heads or tails of Wikidata triples. Filtered MRR ranks each true entity against 500 sampled corrupt heads and 500 sampled corrupt tails that do not form known triples.

Data

The graph contains 2,500,604 retained entities, 535 directed relation types, and 17,137,181 triples extracted from historical Wikidata dumps after filtering rare entities.

Features

Entities are identifiers with learned representations in the standard task; no text or image features are supplied by the core artifact. Relations are typed directed edges.

Splits and evaluation

Triples in the May 2015 snapshot train the model, additions present by August validate it, and additions by November form test. Only entities and relation types already present in May are retained.

Quirks and pitfalls

Wikidata is incomplete and collaboratively edited, so an absent triple is not necessarily false. The predecessor ogbl-wikikg had a negative-sampling bug and is deprecated. Sampled MRR differs from ranking all entities, and inverse-relation augmentation changes the model input.

Sources

OGB coverage note: We have not copied the official OGB leaderboard yet. Where possible, we locate the corresponding papers on arXiv and parse their reported results, so some entries may be missing. We plan to integrate the complete leaderboard soon.

SOTA Progression

new SOTA matches SOTA at that time other proposed result other baseline result

Leaderboard

#ModelMRR ↑Paper
1
InterHT + DigPiece
0.7293 ± 0.0018
2
StarGraph + TripleRE'
0.7290
3
TripleRE + StarGraph
0.7201 ± 0.0011
4
TNCN
0.7110 ± 0.0070
5
InterHT + NodePiece
0.6779 ± 0.0018
6
A*Net
0.6767
7
TripleRE + NodePiece
0.6582 ± 0.0020
8
Qwen3-8B
0.6510
9
Qwen2.5-7B
0.6480
10
ComplEx-RP
0.6392 ± 0.0045
11
ComplEx-RP (50dim)
0.6392 ± 0.0045
12
ComplEx+RP
0.6392
13
Information-Flow (IF) framework
0.6110 ± 0.0110
14
Qwen3-1.7B
0.6070
15
TripleREv2
0.6045 ± 0.0017
16
Mistral-7B-v0.3
0.6040
17
Llama3-8B
0.6040
18
EdgeBank
0.6000
19
PairRE+LRE
0.5970
20
PairRE
0.5805
21
TripleRE
0.5794 ± 0.0020
22
TGN
0.5770 ± 0.0150
23
NodePiece + AutoSF
0.5703 ± 0.0035
24
AutoSF + NodePiece
0.5703 ± 0.0035
25
AutoSF
0.5458 ± 0.0052
26
PairRE
0.5289 ± 0.0030
27
PairRE (200dim)
0.5208 ± 0.0027
28
PairRE
0.5208
29
ComplEx (250dim)
0.5027 ± 0.0027
30
HTGN (UTG)
0.4640 ± 0.0050
31
TransE
0.4536 ± 0.0030
32
RotatE (250dim)
0.4332 ± 0.0025
33
RotatE
0.4332 ± 0.0025
34
RotatE (5×dim)
0.4332 ± 0.0025
35
TransE (500dim)
0.4256 ± 0.0030
36
TransE (5×dim)
0.4256 ± 0.0030
37
TransE
0.4256
38
GPT-4.1-mini
0.4250
39
ComplEx
0.4028 ± 0.0030
40
ComplEx (5×dim)
0.4027 ± 0.0027
41
TGN
0.3960 ± 0.0600
42
GCLSTM (UTG)
0.3740 ± 0.0100
43
DistMult
0.3729 ± 0.0045
44
DistMult (5×dim)
0.3729 ± 0.0045
45
GCN (UTG)
0.3360 ± 0.0090
46
TGAT
0.2820 ± 0.0220
47
DyRep
0.2630 ± 0.0050
48
JODIE
0.2610 ± 0.1230
49
GraphMixer
0.1180 ± 0.0020
SOTA performance set a new SOTA at the time matched the SOTA at the time