Knowledge Graph Completion

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

7 leaderboard tables shown for this task, 7 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

16 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

4 subtasks in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 251 papers with code (482 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.
• Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
  21 Nov 2019 9 repositories listed Syntology ran 2 of 8 samples · 6 unverified · 1 pointer-only (licence)
  HAKE is inspired by the fact that concentric circles in the polar coordinate system can naturally reflect the hierarchy.
• Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey
  8 Feb 2024 6 repositories listed Syntology ran 9 of 18 samples · 9 unverified
  In this survey, we carefully review over 300 articles, focusing on KG-aware research in two principal aspects: KG-driven Multi-Modal (KG4MM) learning, where KGs support multi-modal tasks, and Multi-Modal Knowledge Graph…
• TuckER: Tensor Factorization for Knowledge Graph Completion
  28 Jan 2019 5 repositories listed
  Knowledge graphs are structured representations of real world facts.
• Multi-Relational Embedding for Knowledge Graph Representation and Analysis
  28 Sep 2020 4 repositories listed
  The goal of this thesis is first to study multi-relational embedding on knowledge graphs to propose a new embedding model that explains and improves previous methods, then to study the applications of multi-relational…
• Mining Implicit Entity Preference from User-Item Interaction Data for Knowledge Graph Completion via Adversarial Learning
  28 Mar 2020 4 repositories listed
  Our generator is isolated from user interaction data, and serves to improve the performance of the discriminator.
• Relational Message Passing for Knowledge Graph Completion
  17 Feb 2020 4 repositories listed Syntology ran 1 of 18 samples · 17 unverified
  Specifically, two kinds of neighborhood topology are modeled for a given entity pair under the relational message passing framework: (1) Relational context, which captures the relation types of edges adjacent to the…
• Benchmarking the Abilities of Large Language Models for RDF Knowledge Graph Creation and Comprehension: How Well Do LLMs Speak Turtle?
  29 Sep 2023 3 repositories listed
  Large Language Models (LLMs) are advancing at a rapid pace, with significant improvements at natural language processing and coding tasks.
• Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
  13 Jun 2021 3 repositories listed Syntology ran 2 of 15 samples · 13 unverified
  To further improve the capacity of the path formulation, we propose the Neural Bellman-Ford Network (NBFNet), a general graph neural network framework that solves the path formulation with learned operators in the…
• Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion
  11 Nov 2020 3 repositories listed Syntology ran 0 of 2 samples · 2 unverified · 2 pointer-only (licence)
  Tensor factorization based models have shown great power in knowledge graph completion (KGC).
• KG-BERT: BERT for Knowledge Graph Completion
  7 Sep 2019 3 repositories listed Syntology ran 3 of 4 samples · 1 unverified · 1 pointer-only (licence)
  Knowledge graphs are important resources for many artificial intelligence tasks but often suffer from incompleteness.
• Learning Sequence Encoders for Temporal Knowledge Graph Completion
  10 Sep 2018 3 repositories listed
  In line with previous work on static knowledge graphs, we propose to address this problem by learning latent entity and relation type representations.
• Tokenization, Fusion, and Augmentation: Towards Fine-grained Multi-modal Entity Representation
  15 Apr 2024 2 repositories listed
  To further augment the multi-modal representations, MyGO incorporates fine-grained contrastive learning to highlight the specificity of the entity representations.
• A Foundation Model for Zero-shot Logical Query Reasoning
  10 Apr 2024 2 repositories listed
  Complex logical query answering (CLQA) in knowledge graphs (KGs) goes beyond simple KG completion and aims at answering compositional queries comprised of multiple projections and logical operations.
• HyperFormer: Enhancing Entity and Relation Interaction for Hyper-Relational Knowledge Graph Completion
  12 Aug 2023 2 repositories listed
  Hyper-relational knowledge graph completion (HKGC) aims at inferring unknown triples while considering its qualifiers.
• Dipping PLMs Sauce: Bridging Structure and Text for Effective Knowledge Graph Completion via Conditional Soft Prompting
  4 Jul 2023 2 repositories listed
  However, the fine-tuned PLMs often overwhelmingly focus on the textual information and overlook structural knowledge.
• TransERR: Translation-based Knowledge Graph Embedding via Efficient Relation Rotation
  26 Jun 2023 2 repositories listed
  This paper presents a translation-based knowledge geraph embedding method via efficient relation rotation (TransERR), a straightforward yet effective alternative to traditional translation-based knowledge graph…
• BESS: Balanced Entity Sampling and Sharing for Large-Scale Knowledge Graph Completion
  22 Nov 2022 2 repositories listed Syntology ran 0 of 9 samples · 9 unverified
  We present the award-winning submission to the WikiKG90Mv2 track of OGB-LSC@NeurIPS 2022.
• LambdaKG: A Library for Pre-trained Language Model-Based Knowledge Graph Embeddings
  1 Oct 2022 2 repositories listed
  Knowledge Graphs (KGs) often have two characteristics: heterogeneous graph structure and text-rich entity/relation information.
• SimKGC: Simple Contrastive Knowledge Graph Completion with Pre-trained Language Models
  4 Mar 2022 2 repositories listed Syntology ran 3 of 6 samples · 3 unverified · 3 pointer-only (licence)
  Knowledge graph completion (KGC) aims to reason over known facts and infer the missing links.
• Rethinking Graph Convolutional Networks in Knowledge Graph Completion
  8 Feb 2022 2 repositories listed
  Surprisingly, we observe from experiments that the graph structure modeling in GCNs does not have a significant impact on the performance of KGC models, which is in contrast to the common belief.
• A Probabilistic Framework for Knowledge Graph Data Augmentation
  25 Oct 2021 2 repositories listed
  We present NNMFAug, a probabilistic framework to perform data augmentation for the task of knowledge graph completion to counter the problem of data scarcity, which can enhance the learning process of neural link…
• DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network
  22 Aug 2021 2 repositories listed
  Knowledge graph completion (KGC) has become a focus of attention across deep learning community owing to its excellent contribution to numerous downstream tasks.
• FedE: Embedding Knowledge Graphs in Federated Setting
  24 Oct 2020 2 repositories listed
  Knowledge graphs (KGs) consisting of triples are always incomplete, so it's important to do Knowledge Graph Completion (KGC) by predicting missing triples.
• CoDEx: A Comprehensive Knowledge Graph Completion Benchmark
  16 Sep 2020 2 repositories listed
  We present CoDEx, a set of knowledge graph completion datasets extracted from Wikidata and Wikipedia that improve upon existing knowledge graph completion benchmarks in scope and level of difficulty.
• Multi-Partition Embedding Interaction with Block Term Format for Knowledge Graph Completion
  29 Jun 2020 2 repositories listed
  Knowledge graph embedding methods perform this task by representing entities and relations as embedding vectors and modeling their interactions to compute the matching score of each triple.
• Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs
  8 Jan 2020 2 repositories listed Syntology ran 4 of 6 samples · 2 unverified · 3 pointer-only (licence)
  Large-scale knowledge graphs (KGs) are shown to become more important in current information systems.
• Temporal Knowledge Graph Embedding Model based on Additive Time Series Decomposition
  18 Nov 2019 2 repositories listed
  Moreover, considering the temporal uncertainty during the evolution of entity/relation representations over time, we map the representations of temporal KGs into the space of multi-dimensional Gaussian distributions.
• A Re-evaluation of Knowledge Graph Completion Methods
  10 Nov 2019 2 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  Knowledge Graph Completion (KGC) aims at automatically predicting missing links for large-scale knowledge graphs.
• Diachronic Embedding for Temporal Knowledge Graph Completion
  6 Jul 2019 2 repositories listed
  In this paper, we build novel models for temporal KG completion through equipping static models with a diachronic entity embedding function which provides the characteristics of entities at any point in time.

Syntology lines on 11 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.