class NgramTagger(ContextTagger): (source)
Known subclasses: nltk.tag.sequential.BigramTagger, nltk.tag.sequential.TrigramTagger, nltk.tag.sequential.UnigramTagger
Constructor: NgramTagger(n, train, model, backoff, ...)
A tagger that chooses a token's tag based on its word string and on the preceding n word's tags. In particular, a tuple (tags[i-n:i-1], words[i]) is looked up in a table, and the corresponding tag is returned. N-gram taggers are typically trained on a tagged corpus.
Train a new NgramTagger using the given training data or the supplied model. In particular, construct a new tagger whose table maps from each context (tag[i-n:i-1], word[i]) to the most frequent tag for that context. But exclude any contexts that are already tagged perfectly by the backoff tagger.
| Parameters | |
| train | A tagged corpus consisting of a list of tagged sentences, where each sentence is a list of (word, tag) tuples. |
| backoff | A backoff tagger, to be used by the new tagger if it encounters an unknown context. |
| cutoff | If the most likely tag for a context occurs fewer than cutoff times, then exclude it from the context-to-tag table for the new tagger. |
| Class Method | decode |
Undocumented |
| Method | __init__ |
No summary |
| Method | context |
No summary |
| Method | encode |
Undocumented |
| Class Variable | json |
Undocumented |
| Instance Variable | _n |
Undocumented |
Inherited from ContextTagger:
| Method | __repr__ |
Undocumented |
| Method | choose |
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 | size |
No summary |
| Method | _train |
Initialize this ContextTagger's _context_to_tag table based on the given training data. In particular, for each context c in the training data, set _context_to_tag[c] to the most frequent tag for that context... |
| Instance Variable | _context |
Dictionary mapping contexts to tags. |
Inherited from SequentialBackoffTagger (via ContextTagger):
| 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 |
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 ContextTagger, SequentialBackoffTagger):
| 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 |
Apply self.tag() to each element of sentences. I.e.: |
| Method | _check |
Undocumented |
nltk.tag.sequential.BigramTagger, nltk.tag.sequential.TrigramTagger, nltk.tag.sequential.UnigramTagger| Parameters | |
| n | Undocumented |
| train | Undocumented |
| model | Undocumented |
| backoff | The backoff tagger that should be used for this tagger. |
| cutoff | Undocumented |
| verbose | Undocumented |
| context | A dictionary mapping contexts to tags. |
nltk.tag.sequential.UnigramTagger| Returns | |
| (hashable) | the context that should be used to look up the tag for the specified token; or None if the specified token should not be handled by this tagger. |
nltk.tag.sequential.BigramTagger, nltk.tag.sequential.TrigramTagger, nltk.tag.sequential.UnigramTaggerUndocumented