This is a prototype for a side project idea I had for instructional design; to scrape high-quality articles about interview prep for certain roles to construct a graph of the required skills, interview rounds, and strategies for success. My thought was that knowledge graph construction based on large volumes of text data could help IDs at interview prep companies get a big-picture sense of what interviewees are being told in terms of what to expect and how to ace interviews. I ended up using the REBEL machine learning model for knowledge extraction.
You can read my full write-up of the project and play with the interactive knowledge graph on my GitHub.