Good catch. I'll just post my results. I classified it with a simple algo[1] using the normalized frequency distributions of unigrams and bigrams in the 50-sample training set.
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[1] Using libraries for this like
http://nltk.org/_modules/nltk/classify/naivebayes.html or
http://scikit-learn.org/stable/modules/svm.html would probably be more accurate and faster to implement. Also I didn't cross-validate on the training set, but used new samples.