class nltk.classify.RTEFeatureExtractor(rtepair, stop=True, lemmatize=False)[source]

This builds a bag of words for both the text and the hypothesis after throwing away some stopwords, then calculates overlap and difference.


__init__(rtepair[, stop, lemmatize])
param rtepair:a RTEPair from which features should be extracted
hyp_extra(toktype[, debug]) Compute the extraneous material in the hypothesis.
overlap(toktype[, debug]) Compute the overlap between text and hypothesis.