mlsanityData to 7 Oct 2026

Construction of Hyper-Relational Knowledge Graphs Using Pre-Trained Large Language Models

arXiv 2403.11786 ↗First posted 18 Mar 2024cs.CL cs.AIcited by 2

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Abstract (arXiv)

Extracting hyper-relations is crucial for constructing comprehensive knowledge graphs, but there are limited supervised methods available for this task. To address this gap, we introduce a zero-shot prompt-based method using OpenAI's GPT-3.5 model for extracting hyper-relational knowledge from text. Comparing our model with a baseline, we achieved promising results, with a recall of 0.77. Although our precision is currently lower, a detailed analysis of the model outputs has uncovered potential pathways for future research in this area.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 22 of its 34 references that are in the map. First posted on arXiv 18 Mar 2024.

Builds on

22 of 34 references.

References · 22

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10 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025Large Language Models for Knowledge Graph Embedding: A Surveycited by 3
  2. 2026Construction of Knowledge Graph based on Language Modelcited by 0