curling SPARQL

A quick reference.

I’ve been using the curl utility to retrieve data from SPARQL endpoints for years, but I still have trouble remembering some of the important syntax, so I jotted down a quick reference for myself and I thought I’d share it. I also added some background.

Querying machine learning distributional semantics with SPARQL

Bringing together my two favorite kinds of semantics.

When I wrote Semantic web semantics vs. vector embedding machine learning semantics, I described how distributional semantics–whose machine learning implementations are very popular in modern natural language processing–are quite different from the kind of semantics that RDF people usually talk about. I recently learned of a fascinating project that brings RDF technology and distributional semantics together, letting our SPARQL query logic take advantage of entity similarity as rated…

Playing with wdtaxonomy

Those queries from my last blog entry? Never mind!

After I wrote about Extracting RDF data models from Wikidata in my blog last month, Ettore Rizza suggested that I check out wdtaxonomy, which extracts taxonomies from Wikidata by retrieving the kinds of data that my blog entry’s sample queries retrieved, and it then displays the results as a tree. After playing with it, I’m tempted to tell everyone who read that blog entry to ignore the example queries I included, because you can learn a lot more from wdtaxonomy.

Extracting RDF data models from Wikidata

That's "models", plural.

Some people complain when an RDF dataset lacks a documented data model. A great thing about RDF and SPARQL is that if you want to know what kind of modeling might have been done for a dataset, you just look, even if they’re using non-(W3C-)standard modeling structures. They’re still using triples, so you look at the triples.