Inductive knowledge graph completion

Benchmarks archive 2025-07-28

3 leaderboard tables shown for this task, 3 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

14 shown of 14 papers with code (20 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Inductive Relation Prediction by Subgraph Reasoning
  16 Nov 2019 10 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  The dominant paradigm for relation prediction in knowledge graphs involves learning and operating on latent representations (i.
• Inductive Entity Representations from Text via Link Prediction
  7 Oct 2020 2 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  However, the extent to which these representations learned for link prediction generalize to other tasks is unclear.
• S²DN: Learning to Denoise Unconvincing Knowledge for Inductive Knowledge Graph Completion
  20 Dec 2024 1 repository listed
  These results demonstrate the effectiveness of S²DN in preserving semantic consistency and enhancing the robustness of filtering out unreliable interactions in contaminated KGs.
• Context-aware Inductive Knowledge Graph Completion with Latent Type Constraints and Subgraph Reasoning
  22 Oct 2024 1 repository listed
  With sufficient guidance from proper prompts and supervised fine-tuning, CATS activates the strong semantic understanding and reasoning capabilities of large language models to assess the existence of query triples,…
• Towards Better Benchmark Datasets for Inductive Knowledge Graph Completion
  14 Jun 2024 1 repository listed
  Knowledge Graph Completion (KGC) attempts to predict missing facts in a Knowledge Graph (KG).
• Inductive Knowledge Graph Completion with GNNs and Rules: An Analysis
  14 Aug 2023 1 repository listed
  The task of inductive knowledge graph completion requires models to learn inference patterns from a training graph, which can then be used to make predictions on a disjoint test graph.
• InGram: Inductive Knowledge Graph Embedding via Relation Graphs
  31 May 2023 1 repository listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)
  In this paper, we propose an INductive knowledge GRAph eMbedding method, InGram, that can generate embeddings of new relations as well as new entities at inference time.
• Relational Message Passing for Fully Inductive Knowledge Graph Completion
  8 Oct 2022 1 repository listed
  Subgraph reasoning with message passing is a promising and popular solution.
• StATIK: Structure and Text for Inductive Knowledge Graph Completion
  1 Jul 2022 1 repository listed
  Knowledge graphs (KGs) often represent knowledge bases that are incomplete.
• Building Rule Hierarchies for Efficient Logical Rule Learning from Knowledge Graphs
  29 Jun 2020 1 repository listed
  Many systems have been developed in recent years to mine logical rules from large-scale Knowledge Graphs (KGs), on the grounds that representing regularities as rules enables both the interpretable inference of new…
• Towards Learning Instantiated Logical Rules from Knowledge Graphs
  13 Mar 2020 1 repository listed
  Instantiated rules contain constants extracted from KGs.
• KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
  13 Nov 2019 1 repository listed Syntology ran 1 of 5 samples · 4 unverified · 5 pointer-only (licence)
  Pre-trained language representation models (PLMs) cannot well capture factual knowledge from text.
• DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs
  31 Oct 2019 1 repository listed
  Despite the importance of inductive link prediction, most previous works focused on transductive link prediction and cannot manage previously unseen entities.
• RuDaS: Synthetic Datasets for Rule Learning and Evaluation Tools
  16 Sep 2019 1 repository listed
  Logical rules are a popular knowledge representation language in many domains, representing background knowledge and encoding information that can be derived from given facts in a compact form.

Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.