Papers › Probabilistic Case-based Reasoning for Open-World Knowledge Graph Completion

Probabilistic Case-based Reasoning for Open-World Knowledge Graph Completion

7 Oct 2020Findings of the Association for Computational Linguistics 2020arXiv:2010.03548archive 2025-07-28

Rajarshi Das, Ameya Godbole, Nicholas Monath, Manzil Zaheer, Andrew McCallum

A case-based reasoning (CBR) system solves a new problem by retrieving `cases' that are similar to the given problem. If such a system can achieve high accuracy, it is appealing owing to its simplicity, interpretability, and scalability. In this paper, we demonstrate that such a system is achievable for reasoning in knowledge-bases (KBs). Our approach predicts attributes for an entity by gathering reasoning paths from similar entities in the KB. Our probabilistic model estimates the likelihood that a path is effective at answering a query about the given entity. The parameters of our model can be efficiently computed using simple path statistics and require no iterative optimization. Our model is non-parametric, growing dynamically as new entities and relations are added to the KB. On several benchmark datasets our approach significantly outperforms other rule learning approaches and performs comparably to state-of-the-art embedding-based approaches. Furthermore, we demonstrate the effectiveness of our model in an "open-world" setting where new entities arrive in an online fashion, significantly outperforming state-of-the-art approaches and nearly matching the best offline method. Code available at https://github.com/ameyagodbole/Prob-CBR

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Tasks

Knowledge Graph CompletionLink PredictionWorld Knowledge

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Link Prediction FB122 Prob-CBR HITS@3 74.2 #1 of 5 Archive leaderboard report
Link Prediction FB122 Prob-CBR Hits@10 78.2 #1 of 5 Archive leaderboard report
Link Prediction FB122 Prob-CBR Hits@5 76.0 #1 of 5 Archive leaderboard report
Link Prediction FB122 Prob-CBR MRR 72.7 #1 of 5 Archive leaderboard report
Link Prediction NELL-995 Prob-CBR HITS@3 0.85 #1 of 4 Archive leaderboard report
Link Prediction NELL-995 Prob-CBR Hits@1 0.77 #1 of 4 Archive leaderboard report
Link Prediction NELL-995 Prob-CBR Hits@10 0.89 #1 of 4 Archive leaderboard report
Link Prediction NELL-995 Prob-CBR MRR 0.81 #1 of 4 Archive leaderboard report
Link Prediction WN18RR ProbCBR Hits@1 0.43 #53 of 75 Archive leaderboard report
Link Prediction WN18RR ProbCBR Hits@10 0.55 #53 of 75 Archive leaderboard report
Link Prediction WN18RR ProbCBR Hits@3 0.49 #53 of 75 Archive leaderboard report
Link Prediction WN18RR ProbCBR MRR 0.48 #53 of 75 Archive leaderboard report

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