In my previous post, I talked about the legal / licensing aspects of open linguistic data but there are technical aspects in order for linguistic data to be open too.

I don’t think I’ve ever articulated why I favour a Creative Commons CC-BY-SA license on all my New Testament Greek data.

Adding another potential readbility metric, let’s look at the mean log frequency of dependency paths.

Exactly two weeks ago I said I’d be blogging every day until my talk at SBL. Well, that’s two weeks away so I’m at the half way point. I think the blogging has gone well.

Back in April 2014, Brian Renshaw posted a Good Friday Greek Reader. It was presumably manually produced but I knew such things could be generated automatically and so went about building a system to do so.

In many Greek morphology projects, I’ve wanted a way of conveying the surface form of an inflected word while also conveying the underlying components prior to the application of the sandhi rule. A couple of years ago, I came up with a simple representation for inline annotation.

The parts of speech in a particular language can be drawn up on the basis of syntactic properties, morphological properties, and/or (perhaps most problematically) semantic properties.

What if we just want to classify lexemes in the MorphGNT based on what morphosynactic and morphosemantic features they have?

In a previous post, we looked at which chapters had the highest mean log frequency of lexemes. The code provided there was applicable to other items, though, so let’s now take a look at mean log frequency of forms.

A few years ago, I was introduced by Greg Stump to the notion of distinguishers in morphological description. The analysis of inflected forms in terms of theme + distinguisher is a very helpful concept and one that is made use extensively in my ongoing work on New Testament Greek morphology.

Release 1.1 of GitHub’s Atom Editor fixes a problem I had with using it for polytonic Greek.