# OntoTKGE: Ontology-Enhanced Temporal Knowledge Graph Extrapolation

Source: [OntoTKGE: Ontology-Enhanced Temporal Knowledge Graph Extrapolation](<https://www.sota2.com/research/paper/69d5e0f37d0172140ec75957>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-08-05T05:00:05.795Z

Authors: Dongying Lin, Yinan Liu, Shengwei tang, Bin Wang, Xiaochun Yang

Published: 2026-04-07T06:06:45.000Z

## Abstract

Temporal knowledge graph (TKG) extrapolation is an important task that aims to predict future facts through historical interaction information within KG snapshots. A key challenge for most existing TKG extrapolation models is handling entities with sparse historical interaction. The ontological knowledge is beneficial for alleviating this sparsity issue by enabling these entities to inherit behavioral patterns from other entities with the same concept, which is ignored by previous studies. In this paper, we propose a novel encoder-decoder framework OntoTKGE that leverages the ontological knowledge from the ontology-view KG (i.e., a KG modeling hierarchical relations among abstract concepts as well as the connections between concepts and entities) to guide the TKG extrapolation model's learning process through the effective integration of the ontological and temporal knowledge, thereby enhancing entity embeddings. OntoTKGE is flexible enough to adapt to many TKG extrapolation models. Extensive experiments on five data sets demonstrate that OntoTKGE not only significantly improves the performance of many TKG extrapolation models but also surpasses many state-of-the-art(SOTA) baseline methods.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Temporal Knowledge Graph extrapolation on ICEWS 14](<https://www.sota2.com/research/sota/temporal-knowledge-graph-extrapolation-on-icews-14.md>): Temporal Knowledge Graph extrapolation; ICEWS 14; MRR: 0.601.

- [Temporal Knowledge Graph extrapolation on ICEWS 05-15](<https://www.sota2.com/research/sota/temporal-knowledge-graph-extrapolation-on-icews-05-15.md>): Temporal Knowledge Graph extrapolation; ICEWS 05-15; MRR: 0.7.

- [Temporal Knowledge Graph Forecasting on ICEWS 18](<https://www.sota2.com/research/sota/temporal-knowledge-graph-forecasting-on-icews-18.md>): Temporal Knowledge Graph Forecasting; ICEWS 18; MRR: 0.426.

- [Temporal Knowledge Graph Extrapolation Reasoning on GDELT](<https://www.sota2.com/research/sota/temporal-knowledge-graph-extrapolation-reasoning-on-gdelt.md>): Temporal Knowledge Graph Extrapolation Reasoning; GDELT; MRR: 26.2.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2604.05468>)

[PDF](<https://arxiv.org/pdf/2604.05468.pdf>)