'Given a set of sentences, returns a feature vector for each sentence.
The first $k$ elements are from the `intent_features`,
the rest are {1,0} elements denoting whether an ngram is in sentence.'

def _ngrams_in_sentences(self, examples, ngrams):

    all_vectors = []
    for example in examples:
        presence_vector = self._ngrams_in_sentence(example, ngrams)
        all_vectors.append(presence_vector)
    return all_vectors
