My name is Sindre and I'm a Consultant at Capgemini working with Graphs and Machine Learning.
I'm a recent graduate and the main focus of my bachelor's degree was knowledge graphs, where I mainly worked with representing and analysing news and event data in a semantic knowledge graph.
One important challenge with describing event and news information, is how the description of an event might evolve over time and even be described differently by different sources. This can be differences in which actors are reported to be involved, differing start or end dates, etc.
We used the concept of Annotations and Descriptors to support this. These are nodes used for clustering information related to a report, while still abstracting the information away from the event itself. Thus, allowing possibly conflicting information do describe a single event without introducing logical fallacies.
I'm happy to be part of the community, and looking forward to learning from you as well.