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Trainable lemmatizer docs link (#12795)

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* add an anchor to the trainable lemmatizer section

* add requirement for morphologizer,tagger to rule-based lemmatizer

* morphologizer only
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Sofie Van Landeghem 2023-07-07 15:18:16 +02:00 committed by GitHub
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website/docs/usage/linguistic-features.mdx
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@ -113,7 +113,7 @@ print(doc[2].morph) # 'Case=Nom|Person=2|PronType=Prs'
print(doc[2].pos_) # 'PRON'
```
## Lemmatization {id="lemmatization",model="lemmatizer",version="3"}
## Lemmatization {id="lemmatization",version="3"}
spaCy provides two pipeline components for lemmatization:
@ -170,7 +170,7 @@ nlp = spacy.blank("sv")
nlp.add_pipe("lemmatizer", config={"mode": "lookup"})
```
### Rule-based lemmatizer {id="lemmatizer-rule"}
### Rule-based lemmatizer {id="lemmatizer-rule",model="morphologizer"}
When training pipelines that include a component that assigns part-of-speech
tags (a morphologizer or a tagger with a [POS mapping](#mappings-exceptions)), a
@ -194,7 +194,7 @@ information, without consulting the context of the token. The rule-based
lemmatizer also accepts list-based exception files. For English, these are
acquired from [WordNet](https://wordnet.princeton.edu/).
### Trainable lemmatizer
### Trainable lemmatizer {id="lemmatizer-train",model="trainable_lemmatizer"}
The [`EditTreeLemmatizer`](/api/edittreelemmatizer) can learn form-to-lemma
transformations from a training corpus that includes lemma annotations. This