mirror of https://github.com/explosion/spaCy.git
104 lines
3.5 KiB
Markdown
104 lines
3.5 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.
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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 | Type | Description |
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| --------- | ------------- | ----------------- |
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| `strings` | `StringStore` | The string store. |
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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 UD FEATS format as a string or
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in the tag map dictionary format. Returns the hash of the 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 | Type | Description |
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| ---------- | ------------------ | --------------------------- |
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| `features` | `Union[Dict, str]` | The morphological features. |
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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 FEATS string for the hash of the morphological analysis.
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| Name | Type | Description |
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| ------- | ---- | --------------------------------------- |
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| `morph` | int | The hash of the morphological analysis. |
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## Morphology.feats_to_dict {#feats_to_dict tag="staticmethod"}
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Convert a string FEATS representation to a dictionary of features and values in
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the same format as the 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 | Type | Description |
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| ----------- | ---- | ------------------------------------------------------------------ |
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| `feats` | str | The morphological features in Universal Dependencies FEATS format. |
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| **RETURNS** | dict | The morphological features as a dictionary. |
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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 FEATS 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 | Type | Description |
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| ------------ | ----------------- | --------------------------------------------------------------------- |
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| `feats_dict` | `Dict[str, Dict]` | The morphological features as a dictionary. |
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| **RETURNS** | str | The morphological features as in Universal Dependencies FEATS format. |
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## Attributes {#attributes}
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| Name | Type | Description |
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| ------------- | ----- | -------------------------------------------- |
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| `FEATURE_SEP` | `str` | The FEATS feature separator. Default is `|`. |
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| `FIELD_SEP` | `str` | The FEATS field separator. Default is `=`. |
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| `VALUE_SEP` | `str` | The FEATS value separator. Default is `,`. |
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