DATR, MorphGNT, RDF and Python

I’ve been revisiting DATR, the lexical knowledge representation language, as a possible format for the next generation of [MorphGNT]. I was previously considering developing my own RDF/graph-based format but I suddenly remembered DATR from my student days and it makes a lot more sense to use it rather than try to build my own.

Looking at DATR material, I haven’t seen anything more recent than 1998 so I’m not sure if it’s still the state-of-the-art. It’s a natural fit for some kind of RDFization, something I’m sure I’ll eventually end up doing if someone hasn’t already.

Of course, I’ll have to write Python code to manipulate DATR. Again, unless some already exists. But I’m almost hoping not as I love implementing specs, especially using test-driven development.

UPDATE 2005-04-19: Now see DATR in Python

originally published on jtauber.com

at the intersection of computing, linguistics, philology, and learning science

By day I’m an entrepreneur, web technologist and open-source developer but my academic background is in linguistics (along with some classics, comparative philology, and educational statistics) and my main avocation is working on text, annotations, analysis and software relating to historical languages with a particular interest in facilitating better learning.

While my focus has mostly been on Biblical Greek, much of the work is highly relevant to other Hellenistic Greek texts, other dialects of Ancient Greek and, indeed, texts in completely different languages as well.

All code written for this endeavour is open source and text and data is made available under a Creative Commons license to the extent allowed by the sources used.