---
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"}
Initialize a `Lemmatizer`. Typically, this happens under the hood within spaCy
when a `Language` subclass and its `Vocab` is initialized.
> #### Example
>
> ```python
> from spacy.lemmatizer import Lemmatizer
> from spacy.lookups import Lookups
> lookups = Lookups()
> lookups.add_table("lemma_rules", {"noun": [["s", ""]]})
> lemmatizer = Lemmatizer(lookups)
> ```
>
> For examples of the data format, see the
> [`spacy-lookups-data`](https://github.com/explosion/spacy-lookups-data) repo.
| Name | Type | Description |
| -------------------------------------- | ------------------------- | ------------------------------------------------------------------------------------------------------------------------- |
| `lookups` 2.2 | [`Lookups`](/api/lookups) | The lookups object containing the (optional) tables `"lemma_rules"`, `"lemma_index"`, `"lemma_exc"` and `"lemma_lookup"`. |
| **RETURNS** | `Lemmatizer` | The newly created object. |
## Lemmatizer.\_\_call\_\_ {#call tag="method"}
Lemmatize a string.
> #### Example
>
> ```python
> from spacy.lemmatizer import Lemmatizer
> from spacy.lookups import Lookups
> lookups = Lookups()
> lookups.add_table("lemma_rules", {"noun": [["s", ""]]})
> lemmatizer = Lemmatizer(lookups)
> lemmas = lemmatizer("ducks", "NOUN")
> assert lemmas == ["duck"]
> ```
| Name | Type | Description |
| ------------ | ------------- | -------------------------------------------------------------------------------------------------------- |
| `string` | str | The string to lemmatize, e.g. the token text. |
| `univ_pos` | str / 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 `Lookups`.
> #### Example
>
> ```python
> lookups = Lookups()
> lookups.add_table("lemma_lookup", {"going": "go"})
> assert lemmatizer.lookup("going") == "go"
> ```
| Name | Type | Description |
| ----------- | ---- | ----------------------------------------------------------------------------------------------------------- |
| `string` | str | The string to look up. |
| `orth` | int | Optional hash of the string to look up. If not set, the string will be used and hashed. Defaults to `None`. |
| **RETURNS** | str | 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` | str / 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 |
| -------------------------------------- | ------------------------- | --------------------------------------------------------------- |
| `lookups` 2.2 | [`Lookups`](/api/lookups) | The lookups object containing the rules and data, if available. |