spaCy/website/docs/api/morphology.md

title	tag	source
Morphology	class	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. See MorphAnalysis for the container storing a single morphological analysis.

Morphology.__init__

Create a Morphology object.

Example

from spacy.morphology import Morphology

morphology = Morphology(strings)

Name	Description
strings	The string store. StringStore

Morphology.add

Insert a morphological analysis in the morphology table, if not already present. The morphological analysis may be provided in the Universal Dependencies FEATS format as a string or in the tag map dictionary format. Returns the hash of the new analysis.

Example

feats = "Feat1=Val1|Feat2=Val2"
hash = nlp.vocab.morphology.add(feats)
assert hash == nlp.vocab.strings[feats]

Name	Description
features	The morphological features. Union[Dict, str]

Morphology.get

Example

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	Description
morph	The hash of the morphological analysis. int

Morphology.feats_to_dict

Convert a string FEATS representation to a dictionary of features and values in the same format as the tag map.

Example

from spacy.morphology import Morphology
d = Morphology.feats_to_dict("Feat1=Val1|Feat2=Val2")
assert d == {"Feat1": "Val1", "Feat2": "Val2"}

Name	Description
feats	The morphological features in Universal Dependencies FEATS format. str
RETURNS	The morphological features as a dictionary. Dict[str, str]

Morphology.dict_to_feats

Convert a dictionary of features and values to a string FEATS representation.

Example

from spacy.morphology import Morphology
f = Morphology.dict_to_feats({"Feat1": "Val1", "Feat2": "Val2"})
assert f == "Feat1=Val1|Feat2=Val2"

Name	Description
feats_dict	The morphological features as a dictionary. Dict[str, str]
RETURNS	The morphological features in Universal Dependencies FEATS format. str

Attributes

Name	Description
FEATURE_SEP	The FEATS feature separator. Default is `
FIELD_SEP	The FEATS field separator. Default is =. str
VALUE_SEP	The FEATS value separator. Default is ,. str

MorphAnalysis

Stores a single morphological analysis.

MorphAnalysis.__init__

Initialize a MorphAnalysis object from a Universal Dependencies FEATS string or a dictionary of morphological features.

Example

from spacy.tokens import MorphAnalysis

feats = "Feat1=Val1|Feat2=Val2"
m = MorphAnalysis(nlp.vocab, feats)

Name	Description
vocab	The vocab. Vocab
features	The morphological features. Union[Dict[str, str], str]

MorphAnalysis.__contains__

Whether a feature/value pair is in the analysis.

Example

feats = "Feat1=Val1,Val2|Feat2=Val2"
morph = MorphAnalysis(nlp.vocab, feats)
assert "Feat1=Val1" in morph

Name	Description
RETURNS	A feature/value pair in the analysis. str

MorphAnalysis.__iter__

Iterate over the feature/value pairs in the analysis.

Example

feats = "Feat1=Val1,Val3|Feat2=Val2"
morph = MorphAnalysis(nlp.vocab, feats)
assert list(morph) == ["Feat1=Va1", "Feat1=Val3", "Feat2=Val2"]

Name	Description
YIELDS	A feature/value pair in the analysis. str

MorphAnalysis.__len__

Returns the number of features in the analysis.

Example

feats = "Feat1=Val1,Val2|Feat2=Val2"
morph = MorphAnalysis(nlp.vocab, feats)
assert len(morph) == 3

Name	Description
RETURNS	The number of features in the analysis. int

MorphAnalysis.__str__

Returns the morphological analysis in the Universal Dependencies FEATS string format.

Example

feats = "Feat1=Val1,Val2|Feat2=Val2"
morph = MorphAnalysis(nlp.vocab, feats)
assert str(morph) == feats

Name	Description
RETURNS	The analysis in the Universal Dependencies FEATS format. str

MorphAnalysis.get

Retrieve values for a feature by field.

Example

feats = "Feat1=Val1,Val2"
morph = MorphAnalysis(nlp.vocab, feats)
assert morph.get("Feat1") == ["Val1", "Val2"]

Name	Description
field	The field to retrieve. str
RETURNS	A list of the individual features. List[str]

MorphAnalysis.to_dict

Produce a dict representation of the analysis, in the same format as the tag map.

Example

feats = "Feat1=Val1,Val2|Feat2=Val2"
morph = MorphAnalysis(nlp.vocab, feats)
assert morph.to_dict() == {"Feat1": "Val1,Val2", "Feat2": "Val2"}

Name	Description
RETURNS	The dict representation of the analysis. Dict[str, str]

MorphAnalysis.from_id

Create a morphological analysis from a given hash ID.

Example

feats = "Feat1=Val1|Feat2=Val2"
hash = nlp.vocab.strings[feats]
morph = MorphAnalysis.from_id(nlp.vocab, hash)
assert str(morph) == feats

Name	Description
vocab	The vocab. Vocab
key	The hash of the features string. int