Knowledge Graph Completion

201 papers with code • 7 benchmarks • 16 datasets

Knowledge graphs $G$ are represented as a collection of triples $\{(h, r, t)\}\subseteq E\times R\times E$, where $E$ and $R$ are the entity set and relation set. The task of Knowledge Graph Completion is to either predict unseen relations $r$ between two existing entities: $(h, ?, t)$ or predict the tail entity $t$ given the head entity and the query relation: $(h, r, ?)$.

Source: One-Shot Relational Learning for Knowledge Graphs

Libraries

Use these libraries to find Knowledge Graph Completion models and implementations

Latest papers with no code

Hyper-CL: Conditioning Sentence Representations with Hypernetworks

no code yet • 14 Mar 2024

While the introduction of contrastive learning frameworks in sentence representation learning has significantly contributed to advancements in the field, it still remains unclear whether state-of-the-art sentence embeddings can capture the fine-grained semantics of sentences, particularly when conditioned on specific perspectives.

HDReason: Algorithm-Hardware Codesign for Hyperdimensional Knowledge Graph Reasoning

no code yet • 9 Mar 2024

When conducting cross-models and cross-platforms comparison, HDReason yields an average 4. 2x higher performance and 3. 4x better energy efficiency with similar accuracy versus the state-of-the-art FPGA-based GCN training platform.

Uncertainty-Aware Relational Graph Neural Network for Few-Shot Knowledge Graph Completion

no code yet • 7 Mar 2024

Uncertainty representation is first designed for estimating the uncertainty scope of the entity pairs after transferring feature representations into a Gaussian distribution.

Temporal Knowledge Graph Completion with Time-sensitive Relations in Hypercomplex Space

no code yet • 2 Mar 2024

Temporal knowledge graph completion (TKGC) aims to fill in missing facts within a given temporal knowledge graph at a specific time.

VN Network: Embedding Newly Emerging Entities with Virtual Neighbors

no code yet • 21 Feb 2024

To address this issue, recent works apply the graph neural network on the existing neighbors of the unseen entities.

Knowledge Graph Assisted Automatic Sports News Writing

no code yet • 17 Feb 2024

In this paper, we present a novel method for automatically generating sports news, which employs a unique algorithm that extracts pivotal moments from live text broadcasts and uses them to create an initial draft of the news.

EntailE: Introducing Textual Entailment in Commonsense Knowledge Graph Completion

no code yet • 15 Feb 2024

In this paper, we propose to adopt textual entailment to find implicit entailment relations between CSKG nodes, to effectively densify the subgraph connecting nodes within the same conceptual class, which indicates a similar level of plausibility.

Rendering Graphs for Graph Reasoning in Multimodal Large Language Models

no code yet • 3 Feb 2024

In this paper, we take the first step in incorporating visual information into graph reasoning tasks and propose a new benchmark GITQA, where each sample is a tuple (graph, image, textual description).

Contextualization Distillation from Large Language Model for Knowledge Graph Completion

no code yet • 28 Jan 2024

While textual information significantly enhances the performance of pre-trained language models (PLMs) in knowledge graph completion (KGC), the static and noisy nature of existing corpora collected from Wikipedia articles or synsets definitions often limits the potential of PLM-based KGC models.

Are We Wasting Time? A Fast, Accurate Performance Evaluation Framework for Knowledge Graph Link Predictors

no code yet • 25 Jan 2024

First, we empirically find and theoretically motivate why sampling uniformly at random vastly overestimates the ranking performance of a method.