Our paper on the automated construction of an art-historic KG from unstructured corpora has been accepted at the International Workshop on Knowledge Graph Generation from Text (Text2KG), co-located with the Extended Semantic Web Conference (ESWC 2022). This work was done in collaboration with some of our students from the Knowledge Graphs seminar in SoSe 2021.

Knowledge Graphs (KGs) are a popular way to structure and represent knowledge in a machine-readable way. While KGs serve as the foundation for many applications, the automatic construction of these KGs from texts is a challenging task where Open Information Extraction techniques are prominently leveraged. In this paper, we focus on generating a domain-specific knowledge graph based on art-historic texts from a digitized text collection. We describe the combined use and adaption of existing open information extraction methods to build an art-historic KG that can facilitate data exploration for domain experts. We discuss the challenges that were faced at each step and present detailed error analysis to identify the limitations of existing methods when working with domain-specific corpora.