I am the author of 20+ books, mostly on AI and I have 55 US patents. I have documents AI/semantic web work at SAIC, Disney, Google, Capital One, and Olive AI. Please visit my main web site markwatson.com

There are two versions of the Knowledge Graph Navigator, one is written in Common Lisp and one in Swift. The Common Lisp version is more limitted than the Swift version (also uses a BERT deep learning model for NLP support and features natural language question answering). Both versions are open source and included as example progrtams in two books that I have written:

All of my current eBooks are available for purchase on Lenpub, or if you would like free copies then set the price to "FREE."

The app works by accepting natural language processing (NLP) queries, identifying proper nouns like people, places, organizations, etc. This app then attempts to resolve these entity references to linked data on the DDPedia SPARQL endpoint, verifies with the user that it has found the correct entity references, and then attempts to find as much information and relationships between these entities as it can.

There are three outputs for each query:

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References for Knowledge Graphs

Knowledge Graphs are implemented as directed graphs where nodes can represent people, locations, documents, organizations, business processes, documents on the web, etc. Graph edges represent property relations between nodes. Both nodes and edges can contain named properties.

My other free macOS application KGcreator generates graph data in two formats for both Neo4J and RDF/OWL linked data sources.

I worked as a contractor at Google with their Knowledge Graph. Facebook also has a Knowledge Graph to store information on users and connections. The use of KnowledgeGraphs at smaller organizations is gaining in popularity and I hope that this app will be of some use to you in your work and in learning more about SPARQL.

Here is some reading material:

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