I\'m working on analyzing a large public dataset with lots of verbose human-readable strings that were clearly generated by some regular (in the formal language theory sense
The only thing I can suggest is to play around with Nltk (Natural Language Toolkit for Python) a bit and see if it can at least recognize recurring patterns.
Another thing you may look into is MALLET (Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction etc.)
Perl has something called LinkParser but it seems to require you to provide a representation of the actual grammar (on the other hand, it comes with a large set of different models so maybe it could be shoehorned to help you sorting your samples).
Gate may allow you to create examples from a subset of records in your corpus and possibly reverse engineer the grammar from those.
Finally, have a look at the CRAN repository for text-specific packages.