text: This tutorial is just the entry point to a technology that is entering the*Slope of Enlightenment*in the 
  Gartner technology hype cycle [Gartner Hype Cycle]. Tim Berners-Lee published his paper on the 
  Semantic Web [Berners-Lee 2001] way back in 2001. At least in my experience for most large US 
  corporations the excitement around Machine Learning seemed for a while to eclipse serious interest in 
  OWL, SPARQL, and other Semantic Web technologies in the United States. Then influential technology 
  companies such as Google [Singhal 2012], Facebook [Olanof 2013], and Amazon [Neptune 2017] started 
  to embrace the technology using the term Knowledge Graphs [Noy 2019] and the corporate world is 
  finally realizing that machine learning and knowledge graphs are complimentary not competitive 
  technologies. 
  
  The term knowledge graph itself can be used in different ways. The best definition I’ve heard is that an 
  ontology provides the vocabulary (i.e., essentially the T-Box) and a knowledge graph is an ontology 
  combined with data (A-Box). Although in the corporate world I often hear people simply talk about 
  knowledge graphs without much interest in the distinction between the vocabulary and the data. 