Papers › A Re-evaluation of Knowledge Graph Completion Methods

A Re-evaluation of Knowledge Graph Completion Methods

10 Nov 2019ACL 2020 6arXiv:1911.03903archive 2025-07-28

Zhiqing Sun, Shikhar Vashishth, Soumya Sanyal, Partha Talukdar, Yiming Yang

Knowledge Graph Completion (KGC) aims at automatically predicting missing links for large-scale knowledge graphs. A vast number of state-of-the-art KGC techniques have got published at top conferences in several research fields, including data mining, machine learning, and natural language processing. However, we notice that several recent papers report very high performance, which largely outperforms previous state-of-the-art methods. In this paper, we find that this can be attributed to the inappropriate evaluation protocol used by them and propose a simple evaluation protocol to address this problem. The proposed protocol is robust to handle bias in the model, which can substantially affect the final results. We conduct extensive experiments and report the performance of several existing methods using our protocol. The reproducible code has been made publicly available

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Tasks

Knowledge Graph CompletionKnowledge GraphsLink Prediction

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Link Prediction FB15k-237 ConvKB (Corrected) Hits@10 .421 #71 of 75 Archive leaderboard report
Link Prediction FB15k-237 ConvKB (Corrected) MR 309 #71 of 75 Archive leaderboard report
Link Prediction FB15k-237 ConvKB (Corrected) MRR .309 #71 of 75 Archive leaderboard report
Link Prediction FB15k-237 KBAT (Corrected) Hits@10 .331 #74 of 75 Archive leaderboard report
Link Prediction FB15k-237 KBAT (Corrected) MR 270 #74 of 75 Archive leaderboard report
Link Prediction FB15k-237 KBAT (Corrected) MRR .157 #74 of 75 Archive leaderboard report
Link Prediction FB15k-237 CapsE (Corrected) Hits@10 .057 #75 of 75 Archive leaderboard report
Link Prediction FB15k-237 CapsE (Corrected) MR 446 #75 of 75 Archive leaderboard report
Link Prediction FB15k-237 CapsE (Corrected) MRR .032 #75 of 75 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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