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161 lines
4.2 KiB
Plaintext
161 lines
4.2 KiB
Plaintext
//- 💫 DOCS > API > LEMMATIZER
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include ../_includes/_mixins
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p
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| The #[code Lemmatizer] supports simple part-of-speech-sensitive suffix
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| rules and lookup tables.
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+h(2, "init") Lemmatizer.__init__
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+tag method
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p Create a #[code Lemmatizer].
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+aside-code("Example").
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from spacy.lemmatizer import Lemmatizer
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lemmatizer = Lemmatizer()
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code index]
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+cell dict / #[code None]
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+cell Inventory of lemmas in the language.
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+row
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+cell #[code exceptions]
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+cell dict / #[code None]
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+cell Mapping of string forms to lemmas that bypass the #[code rules].
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+row
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+cell #[code rules]
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+cell dict / #[code None]
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+cell List of suffix rewrite rules.
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+row
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+cell #[code lookup]
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+cell dict / #[code None]
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+cell Lookup table mapping string to their lemmas.
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+row("foot")
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+cell returns
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+cell #[code Lemmatizer]
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+cell The newly created object.
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+h(2, "call") Lemmatizer.__call__
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+tag method
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p Lemmatize a string.
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+aside-code("Example").
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from spacy.lemmatizer import Lemmatizer
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from spacy.lang.en import LEMMA_INDEX, LEMMA_EXC, LEMMA_RULES
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lemmatizer = Lemmatizer(LEMMA_INDEX, LEMMA_EXC, LEMMA_RULES)
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lemmas = lemmatizer(u'ducks', u'NOUN')
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assert lemmas == [u'duck']
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code string]
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+cell unicode
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+cell The string to lemmatize, e.g. the token text.
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+row
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+cell #[code univ_pos]
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+cell unicode / int
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+cell The token's universal part-of-speech tag.
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+row
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+cell #[code morphology]
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+cell dict / #[code None]
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+cell
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| Morphological features following the
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| #[+a("http://universaldependencies.org/") Universal Dependencies]
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| scheme.
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+row("foot")
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+cell returns
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+cell list
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+cell The available lemmas for the string.
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+h(2, "lookup") Lemmatizer.lookup
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+tag method
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+tag-new(2)
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p
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| Look up a lemma in the lookup table, if available. If no lemma is found,
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| the original string is returned. Languages can provide a
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| #[+a("/usage/adding-languages#lemmatizer") lookup table] via the
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| #[code lemma_lookup] variable, set on the individual #[code Language]
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| class.
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+aside-code("Example").
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lookup = {u'going': u'go'}
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lemmatizer = Lemmatizer(lookup=lookup)
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assert lemmatizer.lookup(u'going') == u'go'
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code string]
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+cell unicode
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+cell The string to look up.
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+row("foot")
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+cell returns
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+cell unicode
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+cell The lemma if the string was found, otherwise the original string.
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+h(2, "is_base_form") Lemmatizer.is_base_form
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+tag method
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p
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| Check whether we're dealing with an uninflected paradigm, so we can
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| avoid lemmatization entirely.
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+aside-code("Example").
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pos = 'verb'
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morph = {'VerbForm': 'inf'}
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is_base_form = lemmatizer.is_base_form(pos, morph)
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assert is_base_form == True
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code univ_pos]
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+cell unicode / int
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+cell The token's universal part-of-speech tag.
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+row
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+cell #[code morphology]
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+cell dict
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+cell The token's morphological features.
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+row("foot")
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+cell returns
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+cell bool
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+cell
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| Whether the token's part-of-speech tag and morphological features
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| describe a base form.
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+h(2, "attributes") Attributes
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code index]
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+cell dict / #[code None]
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+cell Inventory of lemmas in the language.
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+row
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+cell #[code exc]
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+cell dict / #[code None]
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+cell Mapping of string forms to lemmas that bypass the #[code rules].
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+row
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+cell #[code rules]
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+cell dict / #[code None]
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+cell List of suffix rewrite rules.
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+row
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+cell #[code lookup_table]
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+tag-new(2)
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+cell dict / #[code None]
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+cell The lemma lookup table, if available.
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