What you have learned in this module is not a lot in terms of notions but has great importance. Together with the type system and data model, the Reasoner is one of the most defining characteristic of Grakn that makes it different from other databases. What you have learned in this module really brings your Grakn game to a different level.
Exercise 1: Logic inference
Think about an example for which a logic inference engine improves the query results of your database.
Exercise 2: A new rule
Add a rule to make the located-in relationship transitive in your knowledge graph. This means, make sure that if A is located in B and B is located in C, you also have that A is located in C.
Load the rule in the knowledge graph and verify that everything has worked by querying for oil platforms located in North America.
After that use the explanation facility on one of the results on the dashboard.
You have reached an important milestone in your Grakn training. You could stop at this point and you would already be able to take advantage of the Grakn software stack. But there is more to Grakn than “just” the database. Now that you are equipped to fully understand them, feel free to examine the numerous examples in the documentation and blog to get more ideas on how to use Grakn. If you want to advance there is one experimental module left.