mirror of https://github.com/explosion/spaCy.git
255 lines
9.5 KiB
Markdown
255 lines
9.5 KiB
Markdown
---
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title: Morphology
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tag: class
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source: spacy/morphology.pyx
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---
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Store the possible morphological analyses for a language, and index them by
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hash. To save space on each token, tokens only know the hash of their
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morphological analysis, so queries of morphological attributes are delegated to
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this class. See [`MorphAnalysis`](/api/morphology#morphanalysis) for the
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container storing a single morphological analysis.
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## Morphology.\_\_init\_\_ {#init tag="method"}
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Create a Morphology object.
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> #### Example
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>
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> ```python
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> from spacy.morphology import Morphology
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>
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> morphology = Morphology(strings)
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> ```
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| Name | Description |
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| --------- | --------------------------------- |
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| `strings` | The string store. ~~StringStore~~ |
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## Morphology.add {#add tag="method"}
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Insert a morphological analysis in the morphology table, if not already present.
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The morphological analysis may be provided in the Universal Dependencies
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[FEATS](https://universaldependencies.org/format.html#morphological-annotation)
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format as a string or in the tag map dictionary format. Returns the hash of the
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new analysis.
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> #### Example
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>
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> ```python
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> feats = "Feat1=Val1|Feat2=Val2"
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> hash = nlp.vocab.morphology.add(feats)
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> assert hash == nlp.vocab.strings[feats]
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> ```
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| Name | Description |
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| ---------- | ------------------------------------------------ |
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| `features` | The morphological features. ~~Union[Dict, str]~~ |
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## Morphology.get {#get tag="method"}
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> #### Example
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>
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> ```python
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> feats = "Feat1=Val1|Feat2=Val2"
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> hash = nlp.vocab.morphology.add(feats)
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> assert nlp.vocab.morphology.get(hash) == feats
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> ```
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Get the
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[FEATS](https://universaldependencies.org/format.html#morphological-annotation)
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string for the hash of the morphological analysis.
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| Name | Description |
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| ------- | ----------------------------------------------- |
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| `morph` | The hash of the morphological analysis. ~~int~~ |
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## Morphology.feats_to_dict {#feats_to_dict tag="staticmethod"}
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Convert a string
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[FEATS](https://universaldependencies.org/format.html#morphological-annotation)
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representation to a dictionary of features and values in the same format as the
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tag map.
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> #### Example
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>
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> ```python
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> from spacy.morphology import Morphology
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> d = Morphology.feats_to_dict("Feat1=Val1|Feat2=Val2")
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> assert d == {"Feat1": "Val1", "Feat2": "Val2"}
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> ```
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| Name | Description |
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| ----------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `feats` | The morphological features in Universal Dependencies [FEATS](https://universaldependencies.org/format.html#morphological-annotation) format. ~~str~~ |
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| **RETURNS** | The morphological features as a dictionary. ~~Dict[str, str]~~ |
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## Morphology.dict_to_feats {#dict_to_feats tag="staticmethod"}
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Convert a dictionary of features and values to a string
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[FEATS](https://universaldependencies.org/format.html#morphological-annotation)
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representation.
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> #### Example
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>
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> ```python
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> from spacy.morphology import Morphology
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> f = Morphology.dict_to_feats({"Feat1": "Val1", "Feat2": "Val2"})
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> assert f == "Feat1=Val1|Feat2=Val2"
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> ```
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| Name | Description |
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| ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `feats_dict` | The morphological features as a dictionary. ~~Dict[str, str]~~ |
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| **RETURNS** | The morphological features as in Universal Dependencies [FEATS](https://universaldependencies.org/format.html#morphological-annotation) format. ~~str~~ |
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## Attributes {#attributes}
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| Name | Description |
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| ------------- | ------------------------------------------------------------------------------------------------------------------------------ |
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| `FEATURE_SEP` | The [FEATS](https://universaldependencies.org/format.html#morphological-annotation) feature separator. Default is `|`. ~~str~~ |
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| `FIELD_SEP` | The [FEATS](https://universaldependencies.org/format.html#morphological-annotation) field separator. Default is `=`. ~~str~~ |
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| `VALUE_SEP` | The [FEATS](https://universaldependencies.org/format.html#morphological-annotation) value separator. Default is `,`. ~~str~~ |
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## MorphAnalysis {#morphanalysis tag="class" source="spacy/tokens/morphanalysis.pyx"}
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Stores a single morphological analysis.
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### MorphAnalysis.\_\_init\_\_ {#morphanalysis-init tag="method"}
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Initialize a MorphAnalysis object from a Universal Dependencies
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[FEATS](https://universaldependencies.org/format.html#morphological-annotation)
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string or a dictionary of morphological features.
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> #### Example
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>
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> ```python
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> from spacy.tokens import MorphAnalysis
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>
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> feats = "Feat1=Val1|Feat2=Val2"
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> m = MorphAnalysis(nlp.vocab, feats)
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> ```
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| Name | Description |
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| ---------- | ---------------------------------------------------------- |
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| `vocab` | The vocab. ~~Vocab~~ |
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| `features` | The morphological features. ~~Union[Dict[str, str], str]~~ |
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### MorphAnalysis.\_\_contains\_\_ {#morphanalysis-contains tag="method"}
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Whether a feature/value pair is in the analysis.
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> #### Example
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>
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> ```python
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> feats = "Feat1=Val1,Val2|Feat2=Val2"
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> morph = MorphAnalysis(nlp.vocab, feats)
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> assert "Feat1=Val1" in morph
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> ```
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| Name | Description |
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| ----------- | --------------------------------------------- |
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| **RETURNS** | A feature/value pair in the analysis. ~~str~~ |
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### MorphAnalysis.\_\_iter\_\_ {#morphanalysis-iter tag="method"}
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Iterate over the feature/value pairs in the analysis.
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> #### Example
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>
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> ```python
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> feats = "Feat1=Val1,Val3|Feat2=Val2"
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> morph = MorphAnalysis(nlp.vocab, feats)
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> assert list(morph) == ["Feat1=Va1", "Feat1=Val3", "Feat2=Val2"]
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> ```
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| Name | Description |
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| ---------- | --------------------------------------------- |
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| **YIELDS** | A feature/value pair in the analysis. ~~str~~ |
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### MorphAnalysis.\_\_len\_\_ {#morphanalysis-len tag="method"}
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Returns the number of features in the analysis.
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> #### Example
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>
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> ```python
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> feats = "Feat1=Val1,Val2|Feat2=Val2"
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> morph = MorphAnalysis(nlp.vocab, feats)
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> assert len(morph) == 3
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> ```
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| Name | Description |
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| ----------- | ----------------------------------------------- |
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| **RETURNS** | The number of features in the analysis. ~~int~~ |
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### MorphAnalysis.\_\_str\_\_ {#morphanalysis-str tag="method"}
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Returns the morphological analysis in the Universal Dependencies
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[FEATS](https://universaldependencies.org/format.html#morphological-annotation)
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string format.
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> #### Example
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>
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> ```python
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> feats = "Feat1=Val1,Val2|Feat2=Val2"
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> morph = MorphAnalysis(nlp.vocab, feats)
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> assert str(morph) == feats
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> ```
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| Name | Description |
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| ----------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
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| **RETURNS** | The analysis in the Universal Dependencies [FEATS](https://universaldependencies.org/format.html#morphological-annotation) format. ~~str~~ |
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### MorphAnalysis.get {#morphanalysis-get tag="method"}
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Retrieve values for a feature by field.
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> #### Example
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>
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> ```python
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> feats = "Feat1=Val1,Val2"
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> morph = MorphAnalysis(nlp.vocab, feats)
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> assert morph.get("Feat1") == ["Val1", "Val2"]
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> ```
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| Name | Description |
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| ----------- | ------------------------------------------------ |
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| `field` | The field to retrieve. ~~str~~ |
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| **RETURNS** | A list of the individual features. ~~List[str]~~ |
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### MorphAnalysis.to_dict {#morphanalysis-to_dict tag="method"}
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Produce a dict representation of the analysis, in the same format as the tag
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map.
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> #### Example
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>
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> ```python
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> feats = "Feat1=Val1,Val2|Feat2=Val2"
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> morph = MorphAnalysis(nlp.vocab, feats)
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> assert morph.to_dict() == {"Feat1": "Val1,Val2", "Feat2": "Val2"}
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> ```
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| Name | Description |
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| ----------- | ----------------------------------------------------------- |
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| **RETURNS** | The dict representation of the analysis. ~~Dict[str, str]~~ |
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### MorphAnalysis.from_id {#morphanalysis-from_id tag="classmethod"}
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Create a morphological analysis from a given hash ID.
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> #### Example
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>
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> ```python
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> feats = "Feat1=Val1|Feat2=Val2"
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> hash = nlp.vocab.strings[feats]
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> morph = MorphAnalysis.from_id(nlp.vocab, hash)
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> assert str(morph) == feats
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> ```
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| Name | Description |
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| ------- | ---------------------------------------- |
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| `vocab` | The vocab. ~~Vocab~~ |
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| `key` | The hash of the features string. ~~int~~ |
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