# Goal of this master thesis

The goal of this master thesis is to explore different applications of semantic networks to fundamental physics. Therefore a variety of approaches will be investigated to structure physics knowledge as a knowledge graph. A special focus will be placed on using modern machine learning methods to generate and evaluate the network data. In particular the following questions should be answered:
* How can semantic networks do justice to the peculiarities of physical knowledge?
* Is it possible to extract the internal physics knowledge of a large language model as semantic network?
* What methods exist to generate physics knowledge graphs?
* What is the quality of the generated data?
* What are [possible applications](possible-applications-of-physics-knowledge-graphs.md) of these methods?