I made a pipe for the srilm server to use with higher order pos n-gram models.  It has only a minimal test.
tidy up non-deterministic bits

Close files immediately when they exit scope (even if they aren't
reference-counted, i.e. because this is running on PyPy). And, sort dicts and
sets whenever our results are influenced by the order they are processed.
The SRILMServerPipe now uses telnetlib, which fixes some subtle problem that was resulting in skipped ngram results from the srilm server.  A couple more cases are tested, and Corrector.py's tests now run successfully under the new model.
SConstruct now uses the 5-gram pos models.
Fixed bug from change to token, tag input: VariationProposer now has to get all possible tags with each token it looks for, since the best tag will not be decided on the fly.
Removed some debug logging from SRILMServerPipe.
use nltk tagger (default) instead of Stanford
Merge branch 'master' of https://github.com/lamber/gc into 5_nltk_tagger

Conflicts:
	SConstruct
Merge branch 'master' of https://github.com/lamber/gc
Merge branch '5_nltk_tagger'
WIP
Now an external corpus is merged in.
bugfixes/tidy-ups for run-em-all.sh
Merge branch 'master' of https://github.com/lamber/gc

Conflicts:
	SConstruct
WIP