I see some of the comments here talk about the code being useless it terms of using it the same way the author of the paper has. Personally for a lot of the papers I have read in NLP based stuff I'd feel more comfortable just having some source to look through to give a better idea of how it was done. Some papers are quiet abstract about their method and aren't really helpful past giving you basic ideas without some…
I'm not sure I agree. In most NLP papers I've read the real meat of the paper is not in the code, but in a couple of equations that, with a lot of mostly-mechanical wrapping around, implementing, debugging, and plugging into well-understood parts should make sense and be a contribution in and of themselves. And for these other things, it might be good to see code a couple of times, but mostly at first, and to get up…
Your right about the classifier, not needing a mention now. My problem starting out of my honours thesis is that I would read something like that then have to go research the thing they have just mentioned in passing because their core audience knows all about it already. So I guess it has an aspect of knowing the best starting point for what you want to research as well.