activity
20232025
most citedBenchmarking the Abilities of Large Language Models for RDF Knowledge Graph Creation and Comprehension: How Well Do LLMs Speak Turtle?

4 citations · 13 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2025

ARUQULA -- An LLM based Text2SPARQL Approach using ReAct and Knowledge Graph Exploration Utilities

Felix Brei, Lorenz Bühmann, Johannes Frey +4

Interacting with knowledge graphs can be a daunting task for people without a background in computer science since the query language that is used (SPARQL) has a high barrier of en…

cs.AI2025

LLM-KG-Bench 3.0: A Compass for SemanticTechnology Capabilities in the Ocean of LLMs

Lars-Peter Meyer, Johannes Frey, Desiree Heim +4

Current Large Language Models (LLMs) can assist developing program code beside many other things, but can they support working with Knowledge Graphs (KGs) as well? Which LLM is off…

cs.DB2024★ 3 cited

Assessing SPARQL capabilities of Large Language Models

Lars-Peter Meyer, Johannes Frey, Felix Brei +1

The integration of Large Language Models (LLMs) with Knowledge Graphs (KGs) offers significant synergistic potential for knowledge-driven applications. One possible integration is…

cs.AI2024★ 2 cited

Leveraging small language models for Text2SPARQL tasks to improve the resilience of AI assistance

Felix Brei, Johannes Frey, Lars-Peter Meyer

In this work we will show that language models with less than one billion parameters can be used to translate natural language to SPARQL queries after fine-tuning. Using three diff…

cs.AI2023★ 4 cited

Benchmarking the Abilities of Large Language Models for RDF Knowledge Graph Creation and Comprehension: How Well Do LLMs Speak Turtle?

Johannes Frey, Lars-Peter Meyer, Natanael Arndt +2

Large Language Models (LLMs) are advancing at a rapid pace, with significant improvements at natural language processing and coding tasks. Yet, their ability to work with formal la…

cs.AI2023★ 4 cited

Developing a Scalable Benchmark for Assessing Large Language Models in Knowledge Graph Engineering

Lars-Peter Meyer, Johannes Frey, Kurt Junghanns +4

As the field of Large Language Models (LLMs) evolves at an accelerated pace, the critical need to assess and monitor their performance emerges. We introduce a benchmarking framewor…