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S. Razniewski

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#natural language process... Preprint Sep 2026

The Canonical Order Problem: When Large Language Models Are Unreliable Knowledge Bases for Multi-Valued Relations

Large language models (LLMs) are increasingly used as knowledge bases (KBs) due to the vast amount of knowledge they acquire during pre-training. While many works focus on extracting single relational triples, most real-world relations are multi-valued and require generating sets of entities. In this paper, we investig...

Timo Pierre Schrader, Annemarie Friedrich, Simon Razniewski et al. · 0 citations
#artificial intelligence Preprint Oct 2025

Auditing a KB Elicitation of Frontier LLM Knowledge: A Multi-dimensional Analysis of GPTKB v1.5

It is found that the models'factual knowledge differs quite significantly from established knowledge bases, and that its accuracy is significantly lower than indicated by previous benchmarks, shedding light on future research opportunities in neuro-symbolic AI concerning extraction, consolidation and verification of fa...

Shrestha Ghosh, Luca Giordano, Yujia Hu et al. · 2 citations
Preprint Aug 2026

Direct Construction of Disambiguated Knowledge Bases from Large Language Models

This work proposes GPTKB 2.0, a methodology for constructing disambiguated KBs directly from large language models (LLMs) that incorporates on-the-fly disambiguation of entities, relations and classes, and is meticulously designed to satisfy both scalability and disambiguation accuracy.

Yujia Hu, Tuan-Phong Nguyen, S. Razniewski · 0 citations
#natural language process... Preprint Sep 2026

LLMPEDIA: Browsing, Verifying, and Comparing the Parametric Encyclopedic Knowledge of LLMs

LLMPEDIA lets visitors inspect this frontier one claim at a time through five one-click views - link-traversal exploration, claim-level factuality, cross-model and political-persona comparison, and a guided topic drill-down - each page, claim, and verdict at a stable URL.

Muhammed Saeed, Simon Razniewski · 0 citations
#natural language process... Preprint Aug 2026

GPTKB 2.0: Browsing, Querying, and Auditing a Disambiguated LLM-Derived Knowledge Base

GPTKB 2.0 performs context-guided disambiguation during recursive KB construction, separating homonyms and merging synonymous mentions as facts are elicited, and makes this process inspectable: users can browse entities, follow links across the KB, and audit the provenance of individual facts.

Yujia Hu, Tuan-Phong Nguyen, Simon Razniewski · 0 citations
#natural language process... Preprint Aug 2026

GPTKB 2.0: Direct Construction of Disambiguated Knowledge Bases from Large Language Models

Automated Knowledge Base Construction (AKBC) is a core NLP task, and recent work proposes generating knowledge bases directly from large language models (LLMs), treating the model itself as the knowledge source. However, LLMs natively possess no representation of entities, leading to duplicate entries as well as confla...

Yujia Hu, Tuan-Phong Nguyen, S. Razniewski · 0 citations

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