Related papers: Schema Generation for Large Knowledge Graphs Using Large Language Models

Schema Generation for Large Knowledge Graphs Using Large Language Models

URL: http://arxiv.org/abs/2506.04512v1
Date: Wed, 04 Jun 2025 23:25:16 GMT
Title: Schema Generation for Large Knowledge Graphs Using Large Language Models
Authors: Bohui Zhang, Yuan He, Lydia Pintscher, Albert Meroño Peñuela, Elena Simperl,
Abstract summary: We explore automatic schema generation using large language models (LLMs)<n>Our benchmark introduces a new challenge for structured generation, pushing the limits of LLMs on syntactically rich formalisms.
Score: 5.764388991407566
License: http://creativecommons.org/licenses/by-nc-sa/4.0/
Abstract: Schemas are vital for ensuring data quality in the Semantic Web and natural language processing. Traditionally, their creation demands substantial involvement from knowledge engineers and domain experts. Leveraging the impressive capabilities of large language models (LLMs) in related tasks like ontology engineering, we explore automatic schema generation using LLMs. To bridge the resource gap, we introduce two datasets: YAGO Schema and Wikidata EntitySchema, along with evaluation metrics. The LLM-based pipelines effectively utilize local and global information from knowledge graphs (KGs) to generate validating schemas in Shape Expressions (ShEx). Experiments demonstrate LLMs' strong potential in producing high-quality ShEx schemas, paving the way for scalable, automated schema generation for large KGs. Furthermore, our benchmark introduces a new challenge for structured generation, pushing the limits of LLMs on syntactically rich formalisms.

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