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