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554df9ef20
* Rename all MDX file to `.mdx`
* Lock current node version (#11885)
* Apply Prettier (#11996)
* Minor website fixes (#11974) [ci skip]
* fix table
* Migrate to Next WEB-17 (#12005)
* Initial commit
* Run `npx create-next-app@13 next-blog`
* Install MDX packages
Following: 77b5f79a4d/packages/next-mdx/readme.md
* Add MDX to Next
* Allow Next to handle `.md` and `.mdx` files.
* Add VSCode extension recommendation
* Disabled TypeScript strict mode for now
* Add prettier
* Apply Prettier to all files
* Make sure to use correct Node version
* Add basic implementation for `MDXRemote`
* Add experimental Rust MDX parser
* Add `/public`
* Add SASS support
* Remove default pages and styling
* Convert to module
This allows to use `import/export` syntax
* Add import for custom components
* Add ability to load plugins
* Extract function
This will make the next commit easier to read
* Allow to handle directories for page creation
* Refactoring
* Allow to parse subfolders for pages
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* Disabled ESLint during builds
* Disabled typescript during build
* Remove Gatsby from `README.md`
* Rephrase Docker part of `README.md`
* Update project structure in `README.md`
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* Add dependencies for plugin
* Use plugin
* Rename wrapper type
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The slugified section ids are useless, because they can not be referenced anywhere anyway. The navigation only works if the section has the same id as the heading.
* Add plugin for custom attributes on Markdown elements
* Add plugin to readd support for tables
* Add plugin to fix problem with wrapped images
For more details see this issue: https://github.com/mdx-js/mdx/issues/1798
* Add necessary meta data to pages
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Before `h1` components where not overwritten and would never have worked and they aren't used anywhere either.
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* Add correct styling
* Fix broken list
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* Implement layout
* Fix links
* Fix broken images
* Fix pattern image
* Fix heading attributes
* Rename heading attribute
`new` was causing some weird issue, so renaming it to `version`
* Update comment syntax in MDX
* Merge imports
* Fix markdown rendering inside components
* Add model pages
* Simplify anchors
* Fix default value for theme
* Add Universe index page
* Add Universe categories
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* Fix Next problem with copy
Next complains when the server renders something different then the client, therfor we move the differing logic to `useEffect`
* Fix improper component nesting
Next doesn't allow block elements inside a `<p>`
* Replace landing page MDX with page component
* Remove inlined iframe content
* Remove ability to inline HTML content in iFrames
* Remove MDX imports
* Fix problem with image inside link in MDX
* Escape character for MDX
* Fix unescaped characters in MDX
* Fix headings with logo
* Allow to export static HTML pages
* Add prebuild script
This command is automatically run by Next
* Replace `svg-loader` with `react-inlinesvg`
`svg-loader` is no longer maintained
* Fix ESLint `react-hooks/exhaustive-deps`
* Fix dropdowns
* Change code language from `cli` to `bash`
* Remove unnessary language `none`
* Fix invalid code language
`markdown_` with an underscore was used to basically turn of syntax highlighting, but using unknown languages know throws an error.
* Enable code blocks plugin
* Readd `InlineCode` component
MDX2 removed the `inlineCode` component
> The special component name `inlineCode` was removed, we recommend to use `pre` for the block version of code, and code for both the block and inline versions
Source: https://mdxjs.com/migrating/v2/#update-mdx-content
* Remove unused code
* Extract function to own file
* Fix code syntax highlighting
* Update syntax for code block meta data
* Remove unused prop
* Fix internal link recognition
There is a problem with regex between Node and browser, and since Next runs the component on both, this create an error.
`Prop `rel` did not match. Server: "null" Client: "noopener nofollow noreferrer"`
This simplifies the implementation and fixes the above error.
* Replace `react-helmet` with `next/head`
* Fix `className` problem for JSX component
* Fix broken bold markdown
* Convert file to `.mjs` to be used by Node process
* Add plugin to replace strings
* Fix custom table row styling
* Fix problem with `span` inside inline `code`
React doesn't allow a `span` inside an inline `code` element and throws an error in dev mode.
* Add `_document` to be able to customize `<html>` and `<body>`
* Add `lang="en"`
* Store Netlify settings in file
This way we don't need to update via Netlify UI, which can be tricky if changing build settings.
* Add sitemap
* Add Smartypants
* Add PWA support
* Add `manifest.webmanifest`
* Fix bug with anchor links after reloading
There was no need for the previous implementation, since the browser handles this nativly. Additional the manual scrolling into view was actually broken, because the heading would disappear behind the menu bar.
* Rename custom event
I was googeling for ages to find out what kind of event `inview` is, only to figure out it was a custom event with a name that sounds pretty much like a native one. 🫠
* Fix missing comment syntax highlighting
* Refactor Quickstart component
The previous implementation was hidding the irrelevant lines via data-props and dynamically generated CSS. This created problems with Next and was also hard to follow. CSS was used to do what React is supposed to handle.
The new implementation simplfy filters the list of children (React elements) via their props.
* Fix syntax highlighting for Training Quickstart
* Unify code rendering
* Improve error logging in Juniper
* Fix Juniper component
* Automatically generate "Read Next" link
* Add Plausible
* Use recent DocSearch component and adjust styling
* Fix images
* Turn of image optimization
> Image Optimization using Next.js' default loader is not compatible with `next export`.
We currently deploy to Netlify via `next export`
* Dont build pages starting with `_`
* Remove unused files
* Add Next plugin to Netlify
* Fix button layout
MDX automatically adds `p` tags around text on a new line and Prettier wants to put the text on a new line. Hacking with JSX string.
* Add 404 page
* Apply Prettier
* Update Prettier for `package.json`
Next sometimes wants to patch `package-lock.json`. The old Prettier setting indended with 4 spaces, but Next always indends with 2 spaces. Since `npm install` automatically uses the indendation from `package.json` for `package-lock.json` and to avoid the format switching back and forth, both files are now set to 2 spaces.
* Apply Next patch to `package-lock.json`
When starting the dev server Next would warn `warn - Found lockfile missing swc dependencies, patching...` and update the `package-lock.json`. These are the patched changes.
* fix link
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* small backslash fixes
* adjust to new style
Co-authored-by: Marcus Blättermann <marcus@essenmitsosse.de>
478 lines
36 KiB
Plaintext
478 lines
36 KiB
Plaintext
---
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title: Token
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teaser: An individual token — i.e. a word, punctuation symbol, whitespace, etc.
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tag: class
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source: spacy/tokens/token.pyx
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---
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## Token.\_\_init\_\_ {id="init",tag="method"}
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Construct a `Token` object.
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> #### Example
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>
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> ```python
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> doc = nlp("Give it back! He pleaded.")
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> token = doc[0]
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> assert token.text == "Give"
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> ```
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| Name | Description |
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| -------- | --------------------------------------------------- |
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| `vocab` | A storage container for lexical types. ~~Vocab~~ |
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| `doc` | The parent document. ~~Doc~~ |
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| `offset` | The index of the token within the document. ~~int~~ |
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## Token.\_\_len\_\_ {id="len",tag="method"}
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The number of unicode characters in the token, i.e. `token.text`.
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> #### Example
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>
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> ```python
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> doc = nlp("Give it back! He pleaded.")
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> token = doc[0]
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> assert len(token) == 4
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> ```
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| Name | Description |
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| ----------- | ------------------------------------------------------ |
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| **RETURNS** | The number of unicode characters in the token. ~~int~~ |
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## Token.set_extension {id="set_extension",tag="classmethod",version="2"}
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Define a custom attribute on the `Token` which becomes available via `Token._`.
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For details, see the documentation on
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[custom attributes](/usage/processing-pipelines#custom-components-attributes).
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> #### Example
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>
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> ```python
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> from spacy.tokens import Token
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> fruit_getter = lambda token: token.text in ("apple", "pear", "banana")
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> Token.set_extension("is_fruit", getter=fruit_getter)
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> doc = nlp("I have an apple")
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> assert doc[3]._.is_fruit
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> ```
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| Name | Description |
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| --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `name` | Name of the attribute to set by the extension. For example, `"my_attr"` will be available as `token._.my_attr`. ~~str~~ |
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| `default` | Optional default value of the attribute if no getter or method is defined. ~~Optional[Any]~~ |
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| `method` | Set a custom method on the object, for example `token._.compare(other_token)`. ~~Optional[Callable[[Token, ...], Any]]~~ |
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| `getter` | Getter function that takes the object and returns an attribute value. Is called when the user accesses the `._` attribute. ~~Optional[Callable[[Token], Any]]~~ |
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| `setter` | Setter function that takes the `Token` and a value, and modifies the object. Is called when the user writes to the `Token._` attribute. ~~Optional[Callable[[Token, Any], None]]~~ |
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| `force` | Force overwriting existing attribute. ~~bool~~ |
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## Token.get_extension {id="get_extension",tag="classmethod",version="2"}
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Look up a previously registered extension by name. Returns a 4-tuple
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`(default, method, getter, setter)` if the extension is registered. Raises a
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`KeyError` otherwise.
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> #### Example
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>
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> ```python
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> from spacy.tokens import Token
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> Token.set_extension("is_fruit", default=False)
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> extension = Token.get_extension("is_fruit")
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> assert extension == (False, None, None, None)
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> ```
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| Name | Description |
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| ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `name` | Name of the extension. ~~str~~ |
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| **RETURNS** | A `(default, method, getter, setter)` tuple of the extension. ~~Tuple[Optional[Any], Optional[Callable], Optional[Callable], Optional[Callable]]~~ |
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## Token.has_extension {id="has_extension",tag="classmethod",version="2"}
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Check whether an extension has been registered on the `Token` class.
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> #### Example
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>
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> ```python
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> from spacy.tokens import Token
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> Token.set_extension("is_fruit", default=False)
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> assert Token.has_extension("is_fruit")
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> ```
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| Name | Description |
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| ----------- | --------------------------------------------------- |
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| `name` | Name of the extension to check. ~~str~~ |
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| **RETURNS** | Whether the extension has been registered. ~~bool~~ |
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## Token.remove_extension {id="remove_extension",tag="classmethod",version="2.0.11"}
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Remove a previously registered extension.
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> #### Example
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>
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> ```python
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> from spacy.tokens import Token
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> Token.set_extension("is_fruit", default=False)
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> removed = Token.remove_extension("is_fruit")
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> assert not Token.has_extension("is_fruit")
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> ```
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| Name | Description |
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| ----------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `name` | Name of the extension. ~~str~~ |
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| **RETURNS** | A `(default, method, getter, setter)` tuple of the removed extension. ~~Tuple[Optional[Any], Optional[Callable], Optional[Callable], Optional[Callable]]~~ |
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## Token.check_flag {id="check_flag",tag="method"}
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Check the value of a boolean flag.
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> #### Example
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>
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> ```python
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> from spacy.attrs import IS_TITLE
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> doc = nlp("Give it back! He pleaded.")
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> token = doc[0]
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> assert token.check_flag(IS_TITLE) == True
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> ```
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| Name | Description |
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| ----------- | ---------------------------------------------- |
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| `flag_id` | The attribute ID of the flag to check. ~~int~~ |
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| **RETURNS** | Whether the flag is set. ~~bool~~ |
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## Token.similarity {id="similarity",tag="method",model="vectors"}
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Compute a semantic similarity estimate. Defaults to cosine over vectors.
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> #### Example
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>
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> ```python
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> apples, _, oranges = nlp("apples and oranges")
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> apples_oranges = apples.similarity(oranges)
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> oranges_apples = oranges.similarity(apples)
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> assert apples_oranges == oranges_apples
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> ```
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| Name | Description |
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| ----------- | -------------------------------------------------------------------------------------------------------------------------------- |
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| other | The object to compare with. By default, accepts `Doc`, `Span`, `Token` and `Lexeme` objects. ~~Union[Doc, Span, Token, Lexeme]~~ |
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| **RETURNS** | A scalar similarity score. Higher is more similar. ~~float~~ |
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## Token.nbor {id="nbor",tag="method"}
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Get a neighboring token.
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> #### Example
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>
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> ```python
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> doc = nlp("Give it back! He pleaded.")
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> give_nbor = doc[0].nbor()
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> assert give_nbor.text == "it"
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> ```
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| Name | Description |
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| ----------- | ------------------------------------------------------------------- |
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| `i` | The relative position of the token to get. Defaults to `1`. ~~int~~ |
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| **RETURNS** | The token at position `self.doc[self.i+i]`. ~~Token~~ |
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## Token.set_morph {id="set_morph",tag="method"}
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Set the morphological analysis from a UD FEATS string, hash value of a UD FEATS
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string, features dict or `MorphAnalysis`. The value `None` can be used to reset
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the morph to an unset state.
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> #### Example
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>
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> ```python
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> doc = nlp("Give it back! He pleaded.")
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> doc[0].set_morph("Mood=Imp|VerbForm=Fin")
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> assert "Mood=Imp" in doc[0].morph
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> assert doc[0].morph.get("Mood") == ["Imp"]
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> ```
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| Name | Description |
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| -------- | --------------------------------------------------------------------------------- |
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| features | The morphological features to set. ~~Union[int, dict, str, MorphAnalysis, None]~~ |
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## Token.has_morph {id="has_morph",tag="method"}
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Check whether the token has annotated morph information. Return `False` when the
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morph annotation is unset/missing.
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| Name | Description |
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| ----------- | --------------------------------------------- |
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| **RETURNS** | Whether the morph annotation is set. ~~bool~~ |
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## Token.is_ancestor {id="is_ancestor",tag="method",model="parser"}
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Check whether this token is a parent, grandparent, etc. of another in the
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dependency tree.
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> #### Example
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>
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> ```python
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> doc = nlp("Give it back! He pleaded.")
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> give = doc[0]
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> it = doc[1]
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> assert give.is_ancestor(it)
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> ```
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| Name | Description |
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| ----------- | -------------------------------------------------------------- |
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| descendant | Another token. ~~Token~~ |
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| **RETURNS** | Whether this token is the ancestor of the descendant. ~~bool~~ |
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## Token.ancestors {id="ancestors",tag="property",model="parser"}
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A sequence of the token's syntactic ancestors (parents, grandparents, etc).
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> #### Example
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>
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> ```python
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> doc = nlp("Give it back! He pleaded.")
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> it_ancestors = doc[1].ancestors
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> assert [t.text for t in it_ancestors] == ["Give"]
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> he_ancestors = doc[4].ancestors
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> assert [t.text for t in he_ancestors] == ["pleaded"]
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> ```
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| Name | Description |
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| ---------- | ------------------------------------------------------------------------------- |
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| **YIELDS** | A sequence of ancestor tokens such that `ancestor.is_ancestor(self)`. ~~Token~~ |
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## Token.conjuncts {id="conjuncts",tag="property",model="parser"}
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A tuple of coordinated tokens, not including the token itself.
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> #### Example
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>
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> ```python
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> doc = nlp("I like apples and oranges")
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> apples_conjuncts = doc[2].conjuncts
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> assert [t.text for t in apples_conjuncts] == ["oranges"]
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> ```
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| Name | Description |
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| ----------- | --------------------------------------------- |
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| **RETURNS** | The coordinated tokens. ~~Tuple[Token, ...]~~ |
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## Token.children {id="children",tag="property",model="parser"}
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A sequence of the token's immediate syntactic children.
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> #### Example
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>
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> ```python
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> doc = nlp("Give it back! He pleaded.")
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> give_children = doc[0].children
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> assert [t.text for t in give_children] == ["it", "back", "!"]
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> ```
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| Name | Description |
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| ---------- | ------------------------------------------------------- |
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| **YIELDS** | A child token such that `child.head == self`. ~~Token~~ |
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## Token.lefts {id="lefts",tag="property",model="parser"}
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The leftward immediate children of the word in the syntactic dependency parse.
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> #### Example
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>
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> ```python
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> doc = nlp("I like New York in Autumn.")
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> lefts = [t.text for t in doc[3].lefts]
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> assert lefts == ["New"]
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> ```
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| Name | Description |
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| ---------- | ------------------------------------ |
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| **YIELDS** | A left-child of the token. ~~Token~~ |
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## Token.rights {id="rights",tag="property",model="parser"}
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The rightward immediate children of the word in the syntactic dependency parse.
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> #### Example
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>
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> ```python
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> doc = nlp("I like New York in Autumn.")
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> rights = [t.text for t in doc[3].rights]
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> assert rights == ["in"]
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> ```
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| Name | Description |
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| ---------- | ------------------------------------- |
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| **YIELDS** | A right-child of the token. ~~Token~~ |
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## Token.n_lefts {id="n_lefts",tag="property",model="parser"}
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The number of leftward immediate children of the word in the syntactic
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dependency parse.
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> #### Example
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>
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> ```python
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> doc = nlp("I like New York in Autumn.")
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> assert doc[3].n_lefts == 1
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> ```
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| Name | Description |
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| ----------- | ---------------------------------------- |
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| **RETURNS** | The number of left-child tokens. ~~int~~ |
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## Token.n_rights {id="n_rights",tag="property",model="parser"}
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The number of rightward immediate children of the word in the syntactic
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dependency parse.
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> #### Example
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>
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> ```python
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> doc = nlp("I like New York in Autumn.")
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> assert doc[3].n_rights == 1
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> ```
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| Name | Description |
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| ----------- | ----------------------------------------- |
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| **RETURNS** | The number of right-child tokens. ~~int~~ |
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## Token.subtree {id="subtree",tag="property",model="parser"}
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A sequence containing the token and all the token's syntactic descendants.
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> #### Example
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>
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> ```python
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> doc = nlp("Give it back! He pleaded.")
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> give_subtree = doc[0].subtree
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> assert [t.text for t in give_subtree] == ["Give", "it", "back", "!"]
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> ```
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| Name | Description |
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| ---------- | ------------------------------------------------------------------------------------ |
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| **YIELDS** | A descendant token such that `self.is_ancestor(token)` or `token == self`. ~~Token~~ |
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## Token.has_vector {id="has_vector",tag="property",model="vectors"}
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A boolean value indicating whether a word vector is associated with the token.
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> #### Example
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>
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> ```python
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> doc = nlp("I like apples")
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> apples = doc[2]
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> assert apples.has_vector
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> ```
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| Name | Description |
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| ----------- | ------------------------------------------------------ |
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| **RETURNS** | Whether the token has a vector data attached. ~~bool~~ |
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## Token.vector {id="vector",tag="property",model="vectors"}
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A real-valued meaning representation.
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> #### Example
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>
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> ```python
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> doc = nlp("I like apples")
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> apples = doc[2]
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> assert apples.vector.dtype == "float32"
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> assert apples.vector.shape == (300,)
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> ```
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| Name | Description |
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| ----------- | ----------------------------------------------------------------------------------------------- |
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| **RETURNS** | A 1-dimensional array representing the token's vector. ~~numpy.ndarray[ndim=1, dtype=float32]~~ |
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## Token.vector_norm {id="vector_norm",tag="property",model="vectors"}
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The L2 norm of the token's vector representation.
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> #### Example
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>
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> ```python
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> doc = nlp("I like apples and pasta")
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> apples = doc[2]
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> pasta = doc[4]
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> apples.vector_norm # 6.89589786529541
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> pasta.vector_norm # 7.759851932525635
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> assert apples.vector_norm != pasta.vector_norm
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> ```
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| Name | Description |
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| ----------- | --------------------------------------------------- |
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| **RETURNS** | The L2 norm of the vector representation. ~~float~~ |
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## Attributes {id="attributes"}
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| Name | Description |
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| ---------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `doc` | The parent document. ~~Doc~~ |
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| `lex` <Tag variant="new">3</Tag> | The underlying lexeme. ~~Lexeme~~ |
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| `sent` | The sentence span that this token is a part of. ~~Span~~ |
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| `text` | Verbatim text content. ~~str~~ |
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| `text_with_ws` | Text content, with trailing space character if present. ~~str~~ |
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| `whitespace_` | Trailing space character if present. ~~str~~ |
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| `orth` | ID of the verbatim text content. ~~int~~ |
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| `orth_` | Verbatim text content (identical to `Token.text`). Exists mostly for consistency with the other attributes. ~~str~~ |
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| `vocab` | The vocab object of the parent `Doc`. ~~vocab~~ |
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| `tensor` | The token's slice of the parent `Doc`'s tensor. ~~numpy.ndarray~~ |
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| `head` | The syntactic parent, or "governor", of this token. ~~Token~~ |
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| `left_edge` | The leftmost token of this token's syntactic descendants. ~~Token~~ |
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| `right_edge` | The rightmost token of this token's syntactic descendants. ~~Token~~ |
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| `i` | The index of the token within the parent document. ~~int~~ |
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| `ent_type` | Named entity type. ~~int~~ |
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| `ent_type_` | Named entity type. ~~str~~ |
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| `ent_iob` | IOB code of named entity tag. `3` means the token begins an entity, `2` means it is outside an entity, `1` means it is inside an entity, and `0` means no entity tag is set. ~~int~~ |
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| `ent_iob_` | IOB code of named entity tag. "B" means the token begins an entity, "I" means it is inside an entity, "O" means it is outside an entity, and "" means no entity tag is set. ~~str~~ |
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| `ent_kb_id` | Knowledge base ID that refers to the named entity this token is a part of, if any. ~~int~~ |
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| `ent_kb_id_` | Knowledge base ID that refers to the named entity this token is a part of, if any. ~~str~~ |
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| `ent_id` | ID of the entity the token is an instance of, if any. Currently not used, but potentially for coreference resolution. ~~int~~ |
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| `ent_id_` | ID of the entity the token is an instance of, if any. Currently not used, but potentially for coreference resolution. ~~str~~ |
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| `lemma` | Base form of the token, with no inflectional suffixes. ~~int~~ |
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| `lemma_` | Base form of the token, with no inflectional suffixes. ~~str~~ |
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| `norm` | The token's norm, i.e. a normalized form of the token text. Can be set in the language's [tokenizer exceptions](/usage/linguistic-features#language-data). ~~int~~ |
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| `norm_` | The token's norm, i.e. a normalized form of the token text. Can be set in the language's [tokenizer exceptions](/usage/linguistic-features#language-data). ~~str~~ |
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| `lower` | Lowercase form of the token. ~~int~~ |
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| `lower_` | Lowercase form of the token text. Equivalent to `Token.text.lower()`. ~~str~~ |
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| `shape` | Transform of the token's string to show orthographic features. Alphabetic characters are replaced by `x` or `X`, and numeric characters are replaced by `d`, and sequences of the same character are truncated after length 4. For example,`"Xxxx"`or`"dd"`. ~~int~~ |
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| `shape_` | Transform of the token's string to show orthographic features. Alphabetic characters are replaced by `x` or `X`, and numeric characters are replaced by `d`, and sequences of the same character are truncated after length 4. For example,`"Xxxx"`or`"dd"`. ~~str~~ |
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| `prefix` | Hash value of a length-N substring from the start of the token. Defaults to `N=1`. ~~int~~ |
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| `prefix_` | A length-N substring from the start of the token. Defaults to `N=1`. ~~str~~ |
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| `suffix` | Hash value of a length-N substring from the end of the token. Defaults to `N=3`. ~~int~~ |
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| `suffix_` | Length-N substring from the end of the token. Defaults to `N=3`. ~~str~~ |
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| `is_alpha` | Does the token consist of alphabetic characters? Equivalent to `token.text.isalpha()`. ~~bool~~ |
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| `is_ascii` | Does the token consist of ASCII characters? Equivalent to `all(ord(c) < 128 for c in token.text)`. ~~bool~~ |
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| `is_digit` | Does the token consist of digits? Equivalent to `token.text.isdigit()`. ~~bool~~ |
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| `is_lower` | Is the token in lowercase? Equivalent to `token.text.islower()`. ~~bool~~ |
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| `is_upper` | Is the token in uppercase? Equivalent to `token.text.isupper()`. ~~bool~~ |
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| `is_title` | Is the token in titlecase? Equivalent to `token.text.istitle()`. ~~bool~~ |
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| `is_punct` | Is the token punctuation? ~~bool~~ |
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| `is_left_punct` | Is the token a left punctuation mark, e.g. `"("` ? ~~bool~~ |
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| `is_right_punct` | Is the token a right punctuation mark, e.g. `")"` ? ~~bool~~ |
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| `is_sent_start` | Does the token start a sentence? ~~bool~~ or `None` if unknown. Defaults to `True` for the first token in the `Doc`. |
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| `is_sent_end` | Does the token end a sentence? ~~bool~~ or `None` if unknown. |
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| `is_space` | Does the token consist of whitespace characters? Equivalent to `token.text.isspace()`. ~~bool~~ |
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| `is_bracket` | Is the token a bracket? ~~bool~~ |
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| `is_quote` | Is the token a quotation mark? ~~bool~~ |
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| `is_currency` | Is the token a currency symbol? ~~bool~~ |
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| `like_url` | Does the token resemble a URL? ~~bool~~ |
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| `like_num` | Does the token represent a number? e.g. "10.9", "10", "ten", etc. ~~bool~~ |
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| `like_email` | Does the token resemble an email address? ~~bool~~ |
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| `is_oov` | Is the token out-of-vocabulary (i.e. does it not have a word vector)? ~~bool~~ |
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| `is_stop` | Is the token part of a "stop list"? ~~bool~~ |
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| `pos` | Coarse-grained part-of-speech from the [Universal POS tag set](https://universaldependencies.org/u/pos/). ~~int~~ |
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| `pos_` | Coarse-grained part-of-speech from the [Universal POS tag set](https://universaldependencies.org/u/pos/). ~~str~~ |
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| `tag` | Fine-grained part-of-speech. ~~int~~ |
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| `tag_` | Fine-grained part-of-speech. ~~str~~ |
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| `morph` <Tag variant="new">3</Tag> | Morphological analysis. ~~MorphAnalysis~~ |
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| `dep` | Syntactic dependency relation. ~~int~~ |
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| `dep_` | Syntactic dependency relation. ~~str~~ |
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| `lang` | Language of the parent document's vocabulary. ~~int~~ |
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| `lang_` | Language of the parent document's vocabulary. ~~str~~ |
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| `prob` | Smoothed log probability estimate of token's word type (context-independent entry in the vocabulary). ~~float~~ |
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| `idx` | The character offset of the token within the parent document. ~~int~~ |
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| `sentiment` | A scalar value indicating the positivity or negativity of the token. ~~float~~ |
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| `lex_id` | Sequential ID of the token's lexical type, used to index into tables, e.g. for word vectors. ~~int~~ |
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| `rank` | Sequential ID of the token's lexical type, used to index into tables, e.g. for word vectors. ~~int~~ |
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| `cluster` | Brown cluster ID. ~~int~~ |
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| `_` | User space for adding custom [attribute extensions](/usage/processing-pipelines#custom-components-attributes). ~~Underscore~~ |
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