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Typo fixes

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Calum Sieppert 2021-07-07 16:53:04 -06:00 committed by GitHub
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website/docs/usage/linguistic-features.md
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@ -512,7 +512,7 @@ nlp = spacy.load("en_core_web_sm", disable=["parser"])
spaCy features an extremely fast statistical entity recognition system, that
assigns labels to contiguous spans of tokens. The default
[trained pipelines](/models) can indentify a variety of named and numeric
[trained pipelines](/models) can identify a variety of named and numeric
entities, including companies, locations, organizations and products. You can
add arbitrary classes to the entity recognition system, and update the model
with new examples.
@ -550,7 +550,7 @@ on a token, it will return an empty string.
> - `I` – Token is **inside** a multi-token entity.
> - `L` – Token is the **last** token of a multi-token entity.
> - `U` – Token is a single-token **unit** entity.
> - `O` – Toke is **outside** an entity.
> - `O` – Token is **outside** an entity.
```python
### {executable="true"}
@ -1498,7 +1498,7 @@ that time, the `Doc` will already be tokenized.
This process of splitting a token requires more settings, because you need to
specify the text of the individual tokens, optional per-token attributes and how
the should be attached to the existing syntax tree. This can be done by
the tokens should be attached to the existing syntax tree. This can be done by
supplying a list of `heads` – either the token to attach the newly split token
to, or a `(token, subtoken)` tuple if the newly split token should be attached
to another subtoken. In this case, "New" should be attached to "York" (the