Unflattening Knowledge Graphs
Marieke van Erp · 2023
Large general-purpose knowledge graphs (KGs) are a critical component for knowledge-driven applications. However, most KGs represent only a limited view of the entities and concepts they describe. The concept coffee can, for example, refer to the plant that yields coffee seeds, the beverage ‘coffee’, and the activity of drinking the beverage. Moreover, it has a long history that is deeply connected to colonialism and status. All of these notions are an intricate part of national identities, have changed dramatically over time, and connect to many different narratives with different opinions on them. This complexity is not captured in current KGs. In this vision paper, I present the three crucial challenges for unflattening knowledge graphs and directions for future work.