14 papers
GPTKB 2.0: Browsing, Querying, and Auditing a Disambiguated LLM-Derived Knowledge Base
Yujia Hu, Tuan-Phong Nguyen, Simon Razniewski
We present a web demo for exploring a large-scale disambiguated knowledge base (KB) materialized from a large language model (LLM). GPTKB 2.0 contains 38.4M triples over 1.6M canon…
GPTKB 2.0: Direct Construction of Disambiguated Knowledge Bases from Large Language Models
Yujia Hu, Tuan-Phong Nguyen, Simon Razniewski
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…
GPTKB v1.5: A Massive Knowledge Base for Exploring Factual LLM Knowledge
Yujia Hu, Tuan-Phong Nguyen, Shrestha Ghosh +2
Language models are powerful artifacts, yet their factual knowledge is still poorly understood, and inaccessible to ad-hoc browsing and scalable statistical analysis. This demonstr…
LLMpedia: A Transparent Framework to Materialize an LLM's Encyclopedic Knowledge at Scale
Muhammed Saeed, Simon Razniewski
Benchmarks like MMLU suggest flagship language models approach factuality saturation above 90\%. \emph{LLMpedia} shows this picture is incomplete. We materialize 1.3M encyc…
Is It Novel and Why? Fine-Grained Patent Novelty Prediction Based on Passage Retrieval
Valentin Knappich, Anna Hätty, Simon Razniewski +1
Novelty assessment is a critical yet complex task in the examination process for patent acceptance, requiring examiners to determine whether an invention is disclosed in a prior ar…
Foundations of LLM Knowledge Materialization: Termination, Reproducibility, Robustness
Luca Giordano, Simon Razniewski
Large Language Models (LLMs) encode substantial factual knowledge, yet measuring and systematizing this knowledge remains challenging. Converting it into structured format, for exa…