Many AI systems need a knowledge base that enables logical inference over the knowledge stored in it. This knowledge base is typically encoded using open standards such as RDF (Resource Description Framework).
To read RDF file, we typically use SPARQL - which is an RDF query language—that is, a semantic query language for databases—able to retrieve and manipulate data stored in RDF.
A simple Python library to use SPARQL - https://sparqlwrapper.readthedocs.io/
Also some other helper classes if you are not comfortable with SPARQL - https://github.com/qcri/RDFframes
Other popular datastores that support RDF formats are GraphDB and Neo4J
The best example of a knowledge base (or graph) is the "Google Knowledge Graph" - a knowledge base used by Google and its services to enhance its search engine's results with information gathered from a variety of sources. The information is presented to users in an infobox next to the search results.
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