Marpa or ParZu?

I spent most of May working through my old natural-language tokenizer, adding a vocabulary-driven lexer/lexicon for German, all in preparation for undertaking a Marpa-based German parser. That's looking halfway decent at this point (except I need to do much better stemming), and then I decided to do a general search on German parsers and found ParZu.

The unusual thing about ParZu, among parsers especially, is that it's fully open source. That is, it has a free license, not a free-for-academics-only license - and it's hosted on GitHub. Also, I can try it online. So I fed it some more-or-less hairy sentences from my current translation in progress - and it parsed them perfectly.

So here's the thing. I kind of want to do my own work and come to terms with the hairiness of things myself. And then on the other hand, parsing German by any means would allow me to jump ahead and maybe start doing translation-related tasks directly....

It's a dilemma.

Update 2014-09-26: Maybe not such a dilemma. ParZu is written in Prolog and I'm just not sure I'm up for that. It honestly seems it would be easier to do it in Marpa...

This is probably incorrect. But I think I'm going to start finding out, this week.

Compiling corpi

So there's this German news corpus obtained between 1996 and 2000 from online retrieval that I intend to use for some of my NLP work, and it occurred to me that I could build a similar corpus (well, the monolingual side of it, anyway) by doing my own periodic retrievals.

To that end, here's the RSS feed pages for the Süddeutsche Zeitung, the Népszabaság Online, and the Népszava (published in New York for Hungarian-Americans).

Analysis of chemical names

Turns out the linguistic structure of chemical names is non-trivial. Unfortunately, as it's also quite profitable, it all seems to be behind paywalls, but I'm visiting Bloomington this summer and will have the opportunity to spend some time in the library, so this is one of the things I hope to make some headway on.

In the meantime, here's a paywalled article from the promisingly named Journal of Chemical Information and Modeling, which describes an early version of Name>Struct, a closed-source interpreter for chemical names that strives to understand them in a way similar to a human chemist - that is, they attempt to model actual usage, not just reflect the official definitions of usage. Descriptive, not prescriptive, chemical linguistics.

Anyway, the folks at CambridgeSoft who make Name>Struct have also highlighted some of the pitfalls of chemical linguistics here.

Ah - silly me. A search on "Name>Struct open source" quickly returns OPSIN, an open-source algorithm that I could probably adapt pretty easily. It's here at BitBucket, and written in (shudder) Java. Nifty Web interface here.

TRADOS 2007 has an OLE dispatch API

I wish I'd known this years ago! TRADOS TagEditor 2007 exposes an OLE API. Workbench doesn't appear to. SDL doesn't support it any more, either. But here are some references to it I ran across the other day. I'm going to try to dump the typelib soon (I have no time at all until Thursday).

• This - from Perl
• This from VB
• This from VB again.

GlobalSight and Microsoft Translator

Two links to software resources: GlobalSight is an open-source translation manager, and this Microsoft Translator page is probably a pretty decent definitive list of who to watch in the industry.

Vocabulary in English

I've been trying to find resources pertaining to the frequency of words in English - surely there must be some kind of graded scale of "commonness" or something? But so far I can't find anything that organized.

Instead, I've got two interesting links here:

• English for Academic Purposes
• 1000 most common SAT words

If we consider each of those and their ilk to be "general vocabulary words", then we'll have that much more luck in identifying technical content in a given document.

TaaS

Terminology as a Service, as envisaged by the Europeans.