nltk.tag.AffixTagger¶
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class
nltk.tag.AffixTagger(train=None, model=None, affix_length=-3, min_stem_length=2, backoff=None, cutoff=0, verbose=False)[source]¶ A tagger that chooses a token’s tag based on a leading or trailing substring of its word string. (It is important to note that these substrings are not necessarily “true” morphological affixes). In particular, a fixed-length substring of the word is looked up in a table, and the corresponding tag is returned. Affix taggers are typically constructed by training them on a tagged corpus.
Construct a new affix tagger.
Parameters: - affix_length – The length of the affixes that should be considered during training and tagging. Use negative numbers for suffixes.
- min_stem_length – Any words whose length is less than min_stem_length+abs(affix_length) will be assigned a tag of None by this tagger.
Methods¶
__init__([train, model, affix_length, ...]) |
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choose_tag(tokens, index, history) |
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context(tokens, index, history) |
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decode_json_obj(obj) |
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encode_json_obj() |
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evaluate(gold) |
Score the accuracy of the tagger against the gold standard. | ||
size() |
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tag(tokens) |
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tag_one(tokens, index, history) |
Determine an appropriate tag for the specified token, and return that tag. | ||
tag_sents(sentences) |
Apply self.tag() to each element of sentences. |
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unicode_repr() |