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.

I think it’s confusing that we name the non-indicative tense-forms with the same terms as indicative tense-forms. For example “present indicative” and “present infinitive”. The word “present” doesn’t mean the same thing in both cases.

Back in July, I thought I’d prototype a REST API for MorphGNT with resources for books, paragraphs, sentences, verses and words.

In a 2008 paper, Wilfred Major constructs what he calls the 50% and 80% vocab lists for Classical Greek. That is, the lemmata that account for 50% and 80% respectively of tokens in the Classical Greek corpus. In this post I provide the code for the equivalent for the Greek New Testament and talk about some of the results.

With dependency paths calculated for the Greek New Testament, we can use mean dependency depth as a proxy for syntactic complexity.

For numerous corpus linguistics applications, it’s useful to have a word-level indication of syntax. A presentation by Vanessa and Robert Gorman gave me the idea of using dependency paths for this purpose so I’ve now calculated them for the GNT based on the GBI syntax trees.