Added some scripts for detecting noun-number errors. These will have to be substantially modified as we figure out how to send queries to our server. The one I was using at work was called TrendStream, so if that name pops up, you'll know what it refers to. Currently, the detect_nn_errors.py script makes use of four different morphological analysis components. This was for testing at work: we wanted to find out which performed the best. For our purposes, I think we can get rid of most of the components and just use Freeling as the default. However, it is a somewhat complicated process to get Freeling running. For one thing, the library is quite large and the code is written in C++. Thus, we would have to make use of SWIG, a wrapper for C++ code. (Despite this, there is a lot of customization that we can do with the actual libraries that Freeling uses, so it's pretty good.) On the other hand, the Perl library Lingua::EN::Inflect is pretty easy to install and use and the performance is comparable. However, there are some weird and unexpected outputs occasionally from Lingua, so I don't know if we definitely should use it. The same could be said for PC-KIMMO, but we might consider that one as well. The evaluate.py script, which will most likely have to be changed drastically eventually, will give you an idea of how the output of the system is evaluated. I threw in the inflect.pl script also, which would be used with the Perl module. It is a very simple script that can be called from inside the Python script to interact with the Perl module. Most likely, there is a much better way of doing that part.