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

Preetha Datta; Fedor Vitiugin; Anastasiia Chizhikova; Nitin Sawhney

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arXiv · 2403.11786

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

Preetha Datta·Fedor Vitiugin·Anastasiia Chizhikova·Nitin Sawhney

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Abstract

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.

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Preetha Datta, Fedor Vitiugin, Anastasiia Chizhikova, Nitin Sawhney. 2024-03-18. Construction of Hyper-Relational Knowledge Graphs Using Pre-Trained Large Language Models. https://arxiv.org/abs/2403.11786

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