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* 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
* Extract logic
* Redirect `index.mdx` to parent directory
* 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`
* Move and rename plugins
* Update plugin for wrapping sections
* Add dependencies for plugin
* Use plugin
* Rename wrapper type
* Simplify unnessary adding of id to sections
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
* Install necessary dependencies
* Remove outdated MDX handling
* Remove reliance on `InlineList`
* Use existing Remark components
* Remove unallowed heading
Before `h1` components where not overwritten and would never have worked and they aren't used anywhere either.
* Add missing components to MDX
* Add correct styling
* Fix broken list
* Fix broken CSS classes
* 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
* Add Universe projects
* 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>
91 lines
9.7 KiB
Plaintext
91 lines
9.7 KiB
Plaintext
The central data structures in spaCy are the [`Language`](/api/language) class,
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the [`Vocab`](/api/vocab) and the [`Doc`](/api/doc) object. The `Language` class
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is used to process a text and turn it into a `Doc` object. It's typically stored
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as a variable called `nlp`. The `Doc` object owns the **sequence of tokens** and
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all their annotations. By centralizing strings, word vectors and lexical
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attributes in the `Vocab`, we avoid storing multiple copies of this data. This
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saves memory, and ensures there's a **single source of truth**.
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Text annotations are also designed to allow a single source of truth: the `Doc`
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object owns the data, and [`Span`](/api/span) and [`Token`](/api/token) are
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**views that point into it**. The `Doc` object is constructed by the
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[`Tokenizer`](/api/tokenizer), and then **modified in place** by the components
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of the pipeline. The `Language` object coordinates these components. It takes
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raw text and sends it through the pipeline, returning an **annotated document**.
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It also orchestrates training and serialization.
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### Container objects {id="architecture-containers"}
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| Name | Description |
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| ----------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| [`Doc`](/api/doc) | A container for accessing linguistic annotations. |
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| [`DocBin`](/api/docbin) | A collection of `Doc` objects for efficient binary serialization. Also used for [training data](/api/data-formats#binary-training). |
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| [`Example`](/api/example) | A collection of training annotations, containing two `Doc` objects: the reference data and the predictions. |
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| [`Language`](/api/language) | Processing class that turns text into `Doc` objects. Different languages implement their own subclasses of it. The variable is typically called `nlp`. |
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| [`Lexeme`](/api/lexeme) | An entry in the vocabulary. It's a word type with no context, as opposed to a word token. It therefore has no part-of-speech tag, dependency parse etc. |
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| [`Span`](/api/span) | A slice from a `Doc` object. |
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| [`SpanGroup`](/api/spangroup) | A named collection of spans belonging to a `Doc`. |
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| [`Token`](/api/token) | An individual token — i.e. a word, punctuation symbol, whitespace, etc. |
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### Processing pipeline {id="architecture-pipeline"}
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The processing pipeline consists of one or more **pipeline components** that are
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called on the `Doc` in order. The tokenizer runs before the components. Pipeline
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components can be added using [`Language.add_pipe`](/api/language#add_pipe).
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They can contain a statistical model and trained weights, or only make
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rule-based modifications to the `Doc`. spaCy provides a range of built-in
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components for different language processing tasks and also allows adding
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[custom components](/usage/processing-pipelines#custom-components).
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| Name | Description |
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| ----------------------------------------------- | ------------------------------------------------------------------------------------------- |
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| [`AttributeRuler`](/api/attributeruler) | Set token attributes using matcher rules. |
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| [`DependencyParser`](/api/dependencyparser) | Predict syntactic dependencies. |
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| [`EditTreeLemmatizer`](/api/edittreelemmatizer) | Predict base forms of words. |
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| [`EntityLinker`](/api/entitylinker) | Disambiguate named entities to nodes in a knowledge base. |
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| [`EntityRecognizer`](/api/entityrecognizer) | Predict named entities, e.g. persons or products. |
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| [`EntityRuler`](/api/entityruler) | Add entity spans to the `Doc` using token-based rules or exact phrase matches. |
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| [`Lemmatizer`](/api/lemmatizer) | Determine the base forms of words using rules and lookups. |
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| [`Morphologizer`](/api/morphologizer) | Predict morphological features and coarse-grained part-of-speech tags. |
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| [`SentenceRecognizer`](/api/sentencerecognizer) | Predict sentence boundaries. |
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| [`Sentencizer`](/api/sentencizer) | Implement rule-based sentence boundary detection that doesn't require the dependency parse. |
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| [`Tagger`](/api/tagger) | Predict part-of-speech tags. |
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| [`TextCategorizer`](/api/textcategorizer) | Predict categories or labels over the whole document. |
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| [`Tok2Vec`](/api/tok2vec) | Apply a "token-to-vector" model and set its outputs. |
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| [`Tokenizer`](/api/tokenizer) | Segment raw text and create `Doc` objects from the words. |
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| [`TrainablePipe`](/api/pipe) | Class that all trainable pipeline components inherit from. |
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| [`Transformer`](/api/transformer) | Use a transformer model and set its outputs. |
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| [Other functions](/api/pipeline-functions) | Automatically apply something to the `Doc`, e.g. to merge spans of tokens. |
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### Matchers {id="architecture-matchers"}
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Matchers help you find and extract information from [`Doc`](/api/doc) objects
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based on match patterns describing the sequences you're looking for. A matcher
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operates on a `Doc` and gives you access to the matched tokens **in context**.
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| Name | Description |
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| --------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| [`DependencyMatcher`](/api/dependencymatcher) | Match sequences of tokens based on dependency trees using [Semgrex operators](https://nlp.stanford.edu/nlp/javadoc/javanlp/edu/stanford/nlp/semgraph/semgrex/SemgrexPattern.html). |
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| [`Matcher`](/api/matcher) | Match sequences of tokens, based on pattern rules, similar to regular expressions. |
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| [`PhraseMatcher`](/api/phrasematcher) | Match sequences of tokens based on phrases. |
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### Other classes {id="architecture-other"}
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| Name | Description |
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| ------------------------------------------------ | -------------------------------------------------------------------------------------------------- |
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| [`Corpus`](/api/corpus) | Class for managing annotated corpora for training and evaluation data. |
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| [`KnowledgeBase`](/api/kb) | Abstract base class for storage and retrieval of data for entity linking. |
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| [`InMemoryLookupKB`](/api/kb_in_memory) | Implementation of `KnowledgeBase` storing all data in memory. |
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| [`Candidate`](/api/kb#candidate) | Object associating a textual mention with a specific entity contained in a `KnowledgeBase`. |
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| [`Lookups`](/api/lookups) | Container for convenient access to large lookup tables and dictionaries. |
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| [`MorphAnalysis`](/api/morphology#morphanalysis) | A morphological analysis. |
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| [`Morphology`](/api/morphology) | Store morphological analyses and map them to and from hash values. |
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| [`Scorer`](/api/scorer) | Compute evaluation scores. |
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| [`StringStore`](/api/stringstore) | Map strings to and from hash values. |
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| [`Vectors`](/api/vectors) | Container class for vector data keyed by string. |
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| [`Vocab`](/api/vocab) | The shared vocabulary that stores strings and gives you access to [`Lexeme`](/api/lexeme) objects. |
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