Triple Classification

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 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

4 datasets 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

23 shown of 23 papers with code (45 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.

• 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.
• 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.
• Reasoning on Knowledge Graphs with Debate Dynamics
  2 Jan 2020 2 repositories listed Syntology ran 0 of 2 samples · 2 unverified
  The main idea is to frame the task of triple classification as a debate game between two reinforcement learning agents which extract arguments -- paths in the knowledge graph -- with the goal to promote the fact being…
• Knowledge Representation Learning: A Quantitative Review
  28 Dec 2018 2 repositories listed
  Knowledge representation learning (KRL) aims to represent entities and relations in knowledge graph in low-dimensional semantic space, which have been widely used in massive knowledge-driven tasks.
• Learning Entity and Relation Embeddings for Knowledge Graph Completion
  25 Jan 2015 2 repositories listed
  Knowledge graph completion aims to perform link prediction between entities.
• Progressive Knowledge Graph Completion
  15 Apr 2024 1 repository listed
  In this paper, we investigate three crucial processes relevant to real-world construction scenarios: (a) the verification process, which arises from the necessity and limitations of human verifiers; (b) the mining…
• Embedding Ontologies via Incorporating Extensional and Intensional Knowledge
  20 Jan 2024 1 repository listed
  Extensional knowledge provides information about the concrete instances that belong to specific concepts in the ontology, while intensional knowledge details inherent properties, characteristics, and semantic…
• A Study on Knowledge Graph Embeddings and Graph Neural Networks for Web Of Things
  23 Oct 2023 1 repository listed
  Graph data structures are widely used to store relational information between several entities.
• Leveraging Pre-trained Language Models for Time Interval Prediction in Text-Enhanced Temporal Knowledge Graphs
  28 Sep 2023 1 repository listed
  Most knowledge graph completion (KGC) methods learn latent representations of entities and relations of a given graph by mapping them into a vector space.
• Exploring Large Language Models for Knowledge Graph Completion
  26 Aug 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Knowledge graphs play a vital role in numerous artificial intelligence tasks, yet they frequently face the issue of incompleteness.
• Iteratively Learning Representations for Unseen Entities with Inter-Rule Correlations
  17 May 2023 1 repository listed
  Recent work on knowledge graph completion (KGC) focused on learning embeddings of entities and relations in knowledge graphs.
• Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer
  3 Mar 2023 1 repository listed
  Through experiments, we justify that the pretrained KGTransformer could be used off the shelf as a general and effective KRF module across KG-related tasks.
• Knowledge Graph Refinement based on Triplet BERT-Networks
  18 Nov 2022 1 repository listed
  This paper adopts a transformer-based triplet network creating an embedding space that clusters the information about an entity or relation in the KG.
• Repurposing Knowledge Graph Embeddings for Triple Representation via Weak Supervision
  22 Aug 2022 1 repository listed
  The majority of knowledge graph embedding techniques treat entities and predicates as separate embedding matrices, using aggregation functions to build a representation of the input triple.
• GreenKGC: A Lightweight Knowledge Graph Completion Method
  19 Aug 2022 1 repository listed
  Knowledge graph completion (KGC) aims to discover missing relationships between entities in knowledge graphs (KGs).
• Language Models as Knowledge Embeddings
  25 Jun 2022 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  In this paper, we propose LMKE, which adopts Language Models to derive Knowledge Embeddings, aiming at both enriching representations of long-tail entities and solving problems of prior description-based methods.
• Differentially Private Federated Knowledge Graphs Embedding
  17 May 2021 1 repository listed
  However, for multiple cross-domain knowledge graphs, state-of-the-art embedding models cannot make full use of the data from different knowledge domains while preserving the privacy of exchanged data.
• TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear Subspaces
  1 Jul 2020 1 repository listed
  We propose TransINT, a novel and interpretable KG embedding method that isomorphically preserves the implication ordering among relations in the embedding space.
• On the Role of Conceptualization in Commonsense Knowledge Graph Construction
  6 Mar 2020 1 repository listed
  Commonsense knowledge graphs (CKGs) like Atomic and ASER are substantially different from conventional KGs as they consist of much larger number of nodes formed by loosely-structured text, which, though, enables them to…
• A Relational Memory-based Embedding Model for Triple Classification and Search Personalization
  13 Jul 2019 1 repository listed
  Knowledge graph embedding methods often suffer from a limitation of memorizing valid triples to predict new ones for triple classification and search personalization problems.
• Differentiating Concepts and Instances for Knowledge Graph Embedding
  12 Nov 2018 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Most conventional knowledge embedding methods encode both entities (concepts and instances) and relations as vectors in a low dimensional semantic space equally, ignoring the difference between concepts and instances.
• Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with Confidence
  9 May 2017 1 repository listed
  Experimental results demonstrate that our confidence-aware models achieve significant and consistent improvements on all tasks, which confirms the capability of CKRL modeling confidence with structural information in…
• Image-embodied Knowledge Representation Learning
  22 Sep 2016 1 repository listed
  More specifically, we first construct representations for all images of an entity with a neural image encoder.

Syntology lines on 5 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.