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99 lines
4.6 KiB
Markdown
99 lines
4.6 KiB
Markdown
---
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title: Lemmatizer
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teaser: Assign the base forms of words
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tag: class
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source: spacy/lemmatizer.py
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---
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The `Lemmatizer` supports simple part-of-speech-sensitive suffix rules and
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lookup tables.
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## Lemmatizer.\_\_init\_\_ {#init tag="method"}
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Create a `Lemmatizer`.
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> #### Example
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>
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> ```python
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> from spacy.lemmatizer import Lemmatizer
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> lemmatizer = Lemmatizer()
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> ```
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| Name | Type | Description |
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| ------------ | ------------- | ---------------------------------------------------------- |
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| `index` | dict / `None` | Inventory of lemmas in the language. |
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| `exceptions` | dict / `None` | Mapping of string forms to lemmas that bypass the `rules`. |
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| `rules` | dict / `None` | List of suffix rewrite rules. |
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| `lookup` | dict / `None` | Lookup table mapping string to their lemmas. |
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| **RETURNS** | `Lemmatizer` | The newly created object. |
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## Lemmatizer.\_\_call\_\_ {#call tag="method"}
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Lemmatize a string.
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> #### Example
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>
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> ```python
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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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> ```
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| Name | Type | Description |
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| ------------ | ------------- | -------------------------------------------------------------------------------------------------------- |
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| `string` | unicode | The string to lemmatize, e.g. the token text. |
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| `univ_pos` | unicode / int | The token's universal part-of-speech tag. |
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| `morphology` | dict / `None` | Morphological features following the [Universal Dependencies](http://universaldependencies.org/) scheme. |
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| **RETURNS** | list | The available lemmas for the string. |
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## Lemmatizer.lookup {#lookup tag="method" new="2"}
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Look up a lemma in the lookup table, if available. If no lemma is found, the
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original string is returned. Languages can provide a
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[lookup table](/usage/adding-languages#lemmatizer) via the `lemma_lookup`
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variable, set on the individual `Language` class.
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> #### Example
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>
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> ```python
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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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> ```
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| Name | Type | Description |
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| ----------- | ------- | ----------------------------------------------------------------- |
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| `string` | unicode | The string to look up. |
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| **RETURNS** | unicode | The lemma if the string was found, otherwise the original string. |
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## Lemmatizer.is_base_form {#is_base_form tag="method"}
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Check whether we're dealing with an uninflected paradigm, so we can avoid
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lemmatization entirely.
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> #### Example
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>
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> ```python
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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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> ```
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| Name | Type | Description |
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| ------------ | ------------- | --------------------------------------------------------------------------------------- |
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| `univ_pos` | unicode / int | The token's universal part-of-speech tag. |
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| `morphology` | dict | The token's morphological features. |
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| **RETURNS** | bool | Whether the token's part-of-speech tag and morphological features describe a base form. |
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## Attributes {#attributes}
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| Name | Type | Description |
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| ----------------------------------------- | ------------- | ---------------------------------------------------------- |
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| `index` | dict / `None` | Inventory of lemmas in the language. |
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| `exc` | dict / `None` | Mapping of string forms to lemmas that bypass the `rules`. |
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| `rules` | dict / `None` | List of suffix rewrite rules. |
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| `lookup_table` <Tag variant="new">2</Tag> | dict / `None` | The lemma lookup table, if available. |
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