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We exploit the Python eco-system to make a GUI for a Prolog program, run with SWI-Prolog, in under 10 minutes

When we start doing knowledge representation in Prolog, we start needing to describe the properties of relations so we can infer more than is in our recorded data. Symmetry, reflexivity and transitivity are the three main relationship properties you'll end up using. In this interactive post we take a look at how they can be encoded.

Knowledge Graphs are a hot topic, no wonder considering how powerful they can be. However, learning how to create, develop, and use them can be a bit of a minefield. In this post we provide a high-level overview and recommend some learning resources.

Simple, classic games like Rock, Paper, Scissors are good to code when learning a new language. The lovely thing about making this game in Prolog is you’re just encoding what it is, not how it is. It’s a subtle difference, but I’ll point it out during this explanation.

Some folks don’t make their data available through RDF formats, or nice SPARQL endpoints, instead they provide a (REST/RESTFUL) API and will return JSON data for your request. It can be a little tricky figuring out how to get this data into your SWI-Prolog program. So in this post I demonstrate with a simple example.