human
Can you provide a code to (b) Der ConsecutiveNPChunker, dessen Code Sie in der nächsten Zelle sehen, basiert auf einem Klassifikator given the following:
(b) Der ConsecutiveNPChunker, dessen Code Sie in der nächsten Zelle sehen, basiert auf einem Klassifikator."
Please write code following the instructions in jupyter notebook style.
assistant
#Here is code to (b) Der ConsecutiveNPChunker, dessen Code Sie in der nächsten Zelle sehen, basiert auf einem Klassifikator.

class ConsecutiveNPChunkTagger(nltk.TaggerI):

    def __init__(self, train_sents, npchunk_features):
        self.extract_features = npchunk_features
        train_set = []
        for tagged_sent in train_sents:
            untagged_sent = nltk.tag.untag(tagged_sent)
            history = []
            for i, (word, tag) in enumerate(tagged_sent):
                featureset = npchunk_features(untagged_sent, i, history)
                train_set.append( (featureset, tag) )
                history.append(tag)
        self.classifier = nltk.NaiveBayesClassifier.train(train_set)

    def tag(self, sentence):
        history = []
        for i, word in enumerate(sentence):
            featureset = self.extract_features(sentence, i, history)
            tag = self.classifier.classify(featureset)
            history.append(tag)
        return zip(sentence, history)

class ConsecutiveNPChunker(nltk.ChunkParserI):
    def __init__(self, train_sents, npchunk_features):
        tagged_sents = [[((w,t),c) for (w,t,c) in
                         nltk.chunk.tree2conlltags(sent)]
                        for sent in train_sents]
        self.tagger = ConsecutiveNPChunkTagger(tagged_sents, npchunk_features)

    def parse(self, sentence):
        tagged_sents = self.tagger.tag(sentence)
        conlltags = [(w,t,c) for ((w,t),c) in tagged_sents]
        return nltk.chunk.conlltags2tree(conlltags)