spaCy/website/docs/api/morphology.md

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---
title: Morphology
tag: class
source: spacy/morphology.pyx
---
Store the possible morphological analyses for a language, and index them
by hash. To save space on each token, tokens only know the hash of their
morphological analysis, so queries of morphological attributes are delegated to
this class.
## Morphology.\_\_init\_\_ {#init tag="method"}
Create a Morphology object using the tag map, lemmatizer and exceptions.
> #### Example
>
> ```python
> from spacy.morphology import Morphology
>
> morphology = Morphology(strings, tag_map, lemmatizer)
> ```
| Name | Type | Description |
| ----------- | ---------------------------------------- | --------------------------------------------------------------------------------------------------------- |
| `strings` | `StringStore` | The string store. |
| `tag_map` | `Dict[str, Dict]` | The tag map. |
| `lemmatizer`| `Lemmatizer` | The lemmatizer. |
| `exc` | `Dict[str, Dict]` | A dictionary of exceptions in the format `{tag: {orth: {"POS": "X", "Feat1": "Val1, "Feat2": "Val2", ...}` |
| **RETURNS** | `Morphology` | The newly constructed object. |
## Morphology.add {#add tag="method"}
Insert a morphological analysis in the morphology table, if not already
present. The morphological analysis may be provided in the UD FEATS format as a
string or in the tag map dictionary format. Returns the hash of the new
analysis.
> #### Example
>
> ```python
> feats = "Feat1=Val1|Feat2=Val2"
> hash = nlp.vocab.morphology.add(feats)
> assert hash == nlp.vocab.strings[feats]
> ```
| Name | Type | Description |
| ----------- | ------------------- | --------------------------- |
| `features` | `Union[Dict, str]` | The morphological features. |
## Morphology.get {#get tag="method"}
> #### Example
>
> ```python
> feats = "Feat1=Val1|Feat2=Val2"
> hash = nlp.vocab.morphology.add(feats)
> assert nlp.vocab.morphology.get(hash) == feats
> ```
Get the FEATS string for the hash of the morphological analysis.
| Name | Type | Description |
| ----------- | ------ | --------------------------------------- |
| `morph` | int | The hash of the morphological analysis. |
## Morphology.load_tag_map {#load_tag_map tag="method"}
Replace the current tag map with the provided tag map.
| Name | Type | Description |
| ----------- | ------------------ | ------------ |
| `tag_map` | `Dict[str, Dict]` | The tag map. |
## Morphology.load_morph_exceptions {#load_morph_exceptions tag="method"}
Replace the current morphological exceptions with the provided exceptions.
| Name | Type | Description |
| ------------- | ------------------ | ----------------------------- |
| `morph_rules` | `Dict[str, Dict]` | The morphological exceptions. |
## Morphology.add_special_case {#add_special_case tag="method"}
Add a special-case rule to the morphological analyzer. Tokens whose tag and
orth match the rule will receive the specified properties.
> #### Example
>
> ```python
> attrs = {"POS": "DET", "Definite": "Def"}
> morphology.add_special_case("DT", "the", attrs)
> ```
| Name | Type | Description |
| ----------- | ---- | ---------------------------------------------- |
| `tag_str` | str | The fine-grained tag. |
| `orth_str` | str | The token text. |
| `attrs` | dict | The features to assign for this token and tag. |
## Morphology.exc {#exc tag="property"}
The current morphological exceptions.
| Name | Type | Description |
| ---------- | ----- | --------------------------------------------------- |
| **YIELDS** | dict | The current dictionary of morphological exceptions. |
## Morphology.lemmatize {#lemmatize tag="method"}
TODO
## Morphology.feats_to_dict {#feats_to_dict tag="staticmethod"}
Convert a string FEATS representation to a dictionary of features and values in
the same format as the tag map.
> #### Example
>
> ```python
> from spacy.morphology import Morphology
> d = Morphology.feats_to_dict("Feat1=Val1|Feat2=Val2")
> assert d == {"Feat1": "Val1", "Feat2": "Val2"}
> ```
| Name | Type | Description |
| ----------- | ---- | ------------------------------------------------------------- |
| `feats` | str | The morphological features in Universal Dependencies FEATS format. |
| **RETURNS** | dict | The morphological features as a dictionary. |
## Morphology.dict_to_feats {#dict_to_feats tag="staticmethod"}
Convert a dictionary of features and values to a string FEATS representation.
> #### Example
>
> ```python
> from spacy.morphology import Morphology
> f = Morphology.dict_to_feats({"Feat1": "Val1", "Feat2": "Val2"})
> assert f == "Feat1=Val1|Feat2=Val2"
> ```
| Name | Type | Description |
| ------------ | ----------------- | --------------------------------------------------------------------- |
| `feats_dict` | `Dict[str, Dict]` | The morphological features as a dictionary. |
| **RETURNS** | str | The morphological features as in Universal Dependencies FEATS format. |
## Attributes {#attributes}
| Name | Type | Description |
| ------------- | ----- | -------------------------------------------- |
| `FEATURE_SEP` | `str` | The FEATS feature separator. Default is `|`. |
| `FIELD_SEP` | `str` | The FEATS field separator. Default is `=`. |
| `VALUE_SEP` | `str` | The FEATS value separator. Default is `,`. |