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 of these methods?