RDF-Based Structured Quality Assessment Representation of Multilingual LLM Evaluations

• URL: http://arxiv.org/abs/2504.21605v1
• Date: Wed, 30 Apr 2025 13:06:40 GMT
• Title: RDF-Based Structured Quality Assessment Representation of Multilingual LLM Evaluations
• Authors: Jonas Gwozdz, Andreas Both,
• Abstract summary: Large Language Models (LLMs) increasingly serve as knowledge interfaces, yet systematically assessing their reliability with conflicting information remains difficult.<n>We propose an RDF-based framework to assess multilingual LLM quality, focusing on knowledge conflicts.
• Score: 0.7666363671957646
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large Language Models (LLMs) increasingly serve as knowledge interfaces, yet systematically assessing their reliability with conflicting information remains difficult. We propose an RDF-based framework to assess multilingual LLM quality, focusing on knowledge conflicts. Our approach captures model responses across four distinct context conditions (complete, incomplete, conflicting, and no-context information) in German and English. This structured representation enables the comprehensive analysis of knowledge leakage-where models favor training data over provided context-error detection, and multilingual consistency. We demonstrate the framework through a fire safety domain experiment, revealing critical patterns in context prioritization and language-specific performance, and demonstrating that our vocabulary was sufficient to express every assessment facet encountered in the 28-question study.

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