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Update docs for Token.morph / Token.set_morph

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Adriane Boyd 2020-10-02 08:48:28 +02:00
parent 65dfaa4f4b
commit fd09e6b140
2 changed files with 92 additions and 77 deletions
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22
website/docs/api/token.md
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@ -172,6 +172,25 @@ Get a neighboring token.
| `i` | The relative position of the token to get. Defaults to `1`. ~~int~~ |
| **RETURNS** | The token at position `self.doc[self.i+i]`. ~~Token~~ |
## Token.set_morph {#set_morph tag="method"}
Set the morphological analysis from a UD FEATS string, hash value of a UD FEATS
string, features dict or `MorphAnalysis`. The value `None` can be used to reset
the morph to an unset state.
> #### Example
>
> ```python
> doc = nlp("Give it back! He pleaded.")
> doc[0].set_morph("Mood=Imp|VerbForm=Fin")
> assert "Mood=Imp" in doc[0].morph
> assert doc[0].morph.get("Mood") == ["Imp"]
> ```
| Name | Description |
| -------- | --------------------------------------------------------------------------------- |
| features | The morphological features to set. ~~Union[int, dict, str, MorphAnalysis, None]~~ |
## Token.is_ancestor {#is_ancestor tag="method" model="parser"}
Check whether this token is a parent, grandparent, etc. of another in the
@ -393,7 +412,7 @@ The L2 norm of the token's vector representation.
## Attributes {#attributes}
| Name | Description |
| -------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| -------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `doc` | The parent document. ~~Doc~~ |
| `lex` <Tag variant="new">3</Tag> | The underlying lexeme. ~~Lexeme~~ |
| `sent` <Tag variant="new">2.0.12</Tag> | The sentence span that this token is a part of. ~~Span~~ |
@ -451,7 +470,6 @@ The L2 norm of the token's vector representation.
| `tag` | Fine-grained part-of-speech. ~~int~~ |
| `tag_` | Fine-grained part-of-speech. ~~str~~ |
| `morph` <Tag variant="new">3</Tag> | Morphological analysis. ~~MorphAnalysis~~ |
| `morph_` <Tag variant="new">3</Tag> | Morphological analysis in the Universal Dependencies [FEATS](https://universaldependencies.org/format.html#morphological-annotation) format. ~~str~~ |
| `dep` | Syntactic dependency relation. ~~int~~ |
| `dep_` | Syntactic dependency relation. ~~str~~ |
| `lang` | Language of the parent document's vocabulary. ~~int~~ |

13
website/docs/usage/linguistic-features.md
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@ -56,16 +56,13 @@ create a surface form. Here are some examples:
Morphological features are stored in the [`MorphAnalysis`](/api/morphanalysis)
under `Token.morph`, which allows you to access individual morphological
features. The attribute `Token.morph_` provides the morphological analysis in
the Universal Dependencies
[FEATS](https://universaldependencies.org/format.html#morphological-annotation)
format.
features.
> #### 📝 Things to try
>
> 1. Change "I" to "She". You should see that the morphological features change
> and express that it's a pronoun in the third person.
> 2. Inspect `token.morph_` for the other tokens.
> 2. Inspect `token.morph` for the other tokens.
```python
### {executable="true"}
@ -75,7 +72,7 @@ nlp = spacy.load("en_core_web_sm")
print("Pipeline:", nlp.pipe_names)
doc = nlp("I was reading the paper.")
token = doc[0] # 'I'
print(token.morph_) # 'Case=Nom|Number=Sing|Person=1|PronType=Prs'
print(token.morph) # 'Case=Nom|Number=Sing|Person=1|PronType=Prs'
print(token.morph.get("PronType")) # ['Prs']
```
@ -91,7 +88,7 @@ import spacy
nlp = spacy.load("de_core_news_sm")
doc = nlp("Wo bist du?") # English: 'Where are you?'
print(doc[2].morph_) # 'Case=Nom|Number=Sing|Person=2|PronType=Prs'
print(doc[2].morph) # 'Case=Nom|Number=Sing|Person=2|PronType=Prs'
print(doc[2].pos_) # 'PRON'
```
@ -117,7 +114,7 @@ import spacy
nlp = spacy.load("en_core_web_sm")
doc = nlp("Where are you?")
print(doc[2].morph_) # 'Case=Nom|Person=2|PronType=Prs'
print(doc[2].morph) # 'Case=Nom|Person=2|PronType=Prs'
print(doc[2].pos_) # 'PRON'
```