nltk.tag.sequential.SequentialBackoffTagger

class documentation

class SequentialBackoffTagger(TaggerI): (source)

Known subclasses: nltk.tag.sequential.ClassifierBasedTagger, nltk.tag.sequential.ContextTagger, nltk.tag.sequential.DefaultTagger, nltk.tag.sequential.RegexpTagger

Constructor: SequentialBackoffTagger(backoff)

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An abstract base class for taggers that tags words sequentially, left to right. Tagging of individual words is performed by the choose_tag() method, which should be defined by subclasses. If a tagger is unable to determine a tag for the specified token, then its backoff tagger is consulted.

Method	`__init__`	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	`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:

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 __init__(self, backoff=None): (source) ¶

overridden in nltk.tag.sequential.ClassifierBasedTagger, nltk.tag.sequential.ContextTagger, nltk.tag.sequential.DefaultTagger, nltk.tag.sequential.RegexpTagger

Undocumented

@abstractmethod
def choose_tag(self, tokens, index, history): (source) ¶

overridden in nltk.tag.sequential.ClassifierBasedTagger, nltk.tag.sequential.ContextTagger, nltk.tag.sequential.DefaultTagger, nltk.tag.sequential.RegexpTagger

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.

Parameters
tokens:list	The list of words that are being tagged.
index:int	The index of the word whose tag should be returned.
history:list(str)	A list of the tags for all words before index.
Returns
str	Undocumented

def tag(self, tokens): (source) ¶

overrides nltk.tag.api.TaggerI.tag

overridden in nltk.tag.sequential.DefaultTagger

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).

Returns
list(tuple(str, str))	Undocumented

def tag_one(self, tokens, index, history): (source) ¶

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.

Parameters
tokens:list	The list of words that are being tagged.
index:int	The index of the word whose tag should be returned.
history:list(str)	A list of the tags for all words before index.
Returns
str	Undocumented

@property
backoff = (source) ¶

overridden in nltk.tag.sequential.BigramTagger, nltk.tag.sequential.TrigramTagger, nltk.tag.sequential.UnigramTagger

The backoff tagger for this tagger.

_taggers = (source) ¶

A list of all the taggers that should be tried to tag a token (i.e., self and its backoff taggers).