One component of many readability measures on texts is the mean log word frequency. Here I do a basic calculation across chapters in the Greek New Testament (with code provided).

In various mailing list posts, blog posts and talks, I’ve shown vocabulary coverage statistics. It’s time to update the code to use more recent data and republish the results here.

It’s exactly four weeks until I’m presenting at the SBL Annual Meeting in Atlanta. As I have a long backlog of posts I’ve wanted to do for a while, I thought I might try to blog every day between now and my talk on November 22nd.

I’ve just finished up registration for the SBL Annual Meeting. Here’s the paper I’ll be presenting.

As helpful as the GBI Syntax Trees are, I have disagreements with them. Randall and Andi are receptive to feedback but there are very different types of disagreement that can arise in syntactic analysis so I thought I’d start to note down what they are.

With one child on each branch identified as the head, a constituent analysis can be converted to a dependency analysis. Fortunately, the GBI syntax trees have an explicit indication of the head, so I went ahead and converted them to a dependency format.

Thanks to Chris Beaven, Paul McLanahan and Michal Čihař, Python 2 support is back in pyuca 1.1.

BibleTech talks were not recorded but I turned on my iPhone's Voice Memo recording and later sync'd the audio with my slides to make this video.

pyuca is my pure Python implementation of the Unicode Collation Algorithm (for sorting, amongst other things, Greek).

I've just released version 1.0 for Python 3.3 and above, and it passes 100% of the UCA conformances tests.

The last three months, I've been working on rebasing the MorphGNT database off the SBLGNT text rather than the UBS3.