5 papers
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…
Characterizing Knowledge Graph Tasks in LLM Benchmarks Using Cognitive Complexity Frameworks
Sara Todorovikj, Lars-Peter Meyer, Michael Martin
Large Language Models (LLMs) are increasingly used for tasks involving Knowledge Graphs (KGs), whose evaluation typically focuses on accuracy and output correctness. We propose a c…
How do Scaling Laws Apply to Knowledge Graph Engineering Tasks? The Impact of Model Size on Large Language Model Performance
Desiree Heim, Lars-Peter Meyer, Markus Schröder +2
When using Large Language Models (LLMs) to support Knowledge Graph Engineering (KGE), one of the first indications when searching for an appropriate model is its size. According to…
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…
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…