nltk.tag.sequential.ClassifierBasedPOSTagger

class documentation

class ClassifierBasedPOSTagger(ClassifierBasedTagger): (source)

Constructor: ClassifierBasedPOSTagger(feature_detector, train, classifier_builder, classifier, ...)

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A classifier based part of speech tagger.

Method feature_detector Return the feature detector that this tagger uses to generate featuresets for its classifier. The feature detector is a function with the signature:

Inherited from ClassifierBasedTagger:

Method __init__ Undocumented
Method __repr__ Undocumented
Method choose_tag Decide which tag should be used for the specified token, and return that tag. If this tagger is unable to determine a tag for the specified token, return None -- do not consult the backoff tagger. This method should be overridden by subclasses of SequentialBackoffTagger.
Method classifier Return the classifier that this tagger uses to choose a tag for each word in a sentence. The input for this classifier is generated using this tagger's feature detector. See feature_detector()
Method _train Build a new classifier, based on the given training data tagged_corpus.
Instance Variable _classifier The classifier used to choose a tag for each token.
Instance Variable _cutoff_prob Cutoff probability for tagging -- if the probability of the most likely tag is less than this, then use backoff.
Instance Variable _feature_detector Undocumented

Inherited from SequentialBackoffTagger (via ClassifierBasedTagger):

Method tag Determine the most appropriate tag sequence for the given token sequence, and return a corresponding list of tagged tokens. A tagged token is encoded as a tuple (token, tag).
Method tag_one Determine an appropriate tag for the specified token, and return that tag. If this tagger is unable to determine a tag for the specified token, then its backoff tagger is consulted.
Property backoff The backoff tagger for this tagger.
Instance Variable _taggers A list of all the taggers that should be tried to tag a token (i.e., self and its backoff taggers).

Inherited from TaggerI (via ClassifierBasedTagger, SequentialBackoffTagger, FeaturesetTaggerI):

Method evaluate Score the accuracy of the tagger against the gold standard. Strip the tags from the gold standard text, retag it using the tagger, then compute the accuracy score.
Method tag_sents Apply self.tag() to each element of sentences. I.e.:
Method _check_params Undocumented
def feature_detector(self, tokens, index, history): (source) ΒΆ
overrides nltk.tag.sequential.ClassifierBasedTagger.feature_detector

Return the feature detector that this tagger uses to generate featuresets for its classifier. The feature detector is a function with the signature:

feature_detector(tokens, index, history) -> featureset

See classifier()