English WordNet is a representation of the English language a lexical network. It groups words into synsets and links them according to semantic relationships such as hypernymy, antonymy and meronymy. You can actually browse through its content from the English Wordnet website. Wordnet is often used in natural language processing (NLP) applications (but also many others) and provides deep lexical information about the English language as a graph. As a graph… that sounds interesting, definitely worth a QuickGraph.
Because this is a particularly rich case I’ll break it down in at least two instalments. In the first one I’ll explain the construction of the graph in Neo4j and in the second one I’ll show some interesting ways of using it. I hope you’ll enjoy it.
Continue reading “QuickGraph#16 The English WordNet in Neo4j (part 1)” →
You’ve probably heard that there are billions of pages on the web that embed structured data describing products, events, people, organisations… One of the most popular mechanisms for doing this is JSON-LD which is one of the many ways of serialising triples. Since you’re here, I’m sure you know that triples form graphs and that I like exploring graphy things…
In this QuickGraph I’ll have a look at the brand new White House pages and use Neo4j and neosemantics to analyse the structured data they embed.
Continue reading “QuickGraph#15 Analysing the structured data embedded in web pages” →
Neosemantics (n10s) has been supporting RDF* for a few months now (from release 4.1.0, Sep 2020). Around the time of the release we did a live coding session going over some of the new features, one of which was RDF*. I thought I’d put a couple of examples in a quick graph similar to the ones in the video session to make it easier for people to find and give it a try. This is what you’re reading right now.
Continue reading “QuickGraph#14 Using RDF* with Neo4j” →