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

Preetha Datta, Fedor Vitiugin, Anastasiia Chizhikova, Nitin Sawhney
3/18/2024
cs.CLcs.AI

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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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Cite this paper

@article{datta2024construction,
  title  = {Construction of Hyper-Relational Knowledge Graphs Using Pre-Trained Large Language Models},
  author = {Preetha Datta and Fedor Vitiugin and Anastasiia Chizhikova and Nitin Sawhney},
  year   = {2024},
  eprint = {2403.11786},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.11786v1}
}

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