mlsanityData to 14 Oct 2026

GPTKB v1.5: A Massive Knowledge Base for Exploring Factual LLM Knowledge

arXiv 2507.05740 ↗First posted 8 Jul 2025cs.CLcited by 5

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Abstract (arXiv)

Language models are powerful artifacts, yet their factual knowledge is still poorly understood, and inaccessible to ad-hoc browsing and scalable statistical analysis. This demonstration introduces GPTKB v1.5, a densely interlinked 100-million-triple knowledge base (KB) built for 14,000 from GPT-4.1, using the GPTKB methodology for massive-recursive LLM knowledge materialization. This demo focuses on three use cases: (1) link-traversal-based LLM knowledge exploration, (2) SPARQL-based structured LLM knowledge querying, (3) comparative exploration of the strengths and weaknesses of LLM knowledge. Massive-recursive LLM knowledge materialization is a groundbreaking opportunity both for the systematic analysis of LLM knowledge, as well as for automated KB construction.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 11 of its 18 references that are in the map. First posted on arXiv 8 Jul 2025.

Builds on

11 of 18 references.

References · 11

  1. 2019Language Models as Knowledge Bases?cited by 1,936
  2. 2019How Can We Know What Language Models Know?cited by 959
  3. 2020How Much Knowledge Can You Pack Into the Parameters of a Language Model?cited by 719
  4. 2019CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Datacited by 548
  5. 2023The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A"cited by 407
  6. 2023Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?cited by 168
  7. 2023Crawling the Internal Knowledge-Base of Language Modelscited by 85
  8. 2021Can Generative Pre-trained Language Models Serve as Knowledge Bases for Closed-book QA?cited by 62
  9. 2020Machine Knowledge: Creation and Curation of Comprehensive Knowledge Basescited by 55
  10. 2024Enabling LLM Knowledge Analysis via Extensive Materializationcited by 12
  11. 2023Evaluating the Knowledge Base Completion Potential of GPTcited by 9

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 3.

5 papers.

  1. 2025Foundations of LLM Knowledge Materialization: Termination, Reproducibility, Robustnesscited by 3
  2. 2025Auditing a KB Elicitation of Frontier LLM Knowledge: A Multi-dimensional Analysis of GPTKB v1.5cited by 3
  3. 2026LLMpedia: A Transparent Framework to Materialize an LLM's Encyclopedic Knowledge at Scalecited by 3
  4. 2026Beyond Questions: Evaluating the Stated Knowledge of LLMscited by 1
  5. 2026GPTKB 2.0: Browsing, Querying, and Auditing a Disambiguated LLM-Derived Knowledge Basecited by 0