Construction of Hyper-Relational Knowledge Graphs Using Pre-Trained Large Language Models
<|reference_start|>Construction of Hyper-Relational Knowledge Graphs Using Pre-Trained Large Language Models: 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.<|reference_end|>
@article{datta2024construction,
    title={Construction of Hyper-Relational Knowledge Graphs Using Pre-Trained
  Large Language Models},
    author={Preetha Datta, Fedor Vitiugin, Anastasiia Chizhikova, Nitin Sawhney},
    journal={arXiv preprint arXiv:2403.11786},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.11786},
    primaryClass={cs.CL cs.AI}
}