Update docs [ci skip]

website/docs/usage/_benchmarks-models.md

@@ -7,13 +7,14 @@ import { Help } from 'components/typography'; import Link from 'components/link'
 | Pipeline                                                   | Parser | Tagger |  NER | WPS<br />CPU <Help>words per second on CPU, higher is better</Help> | WPS<br/>GPU <Help>words per second on GPU, higher is better</Help> |
 | ---------------------------------------------------------- | -----: | -----: | ---: | ------------------------------------------------------------------: | -----------------------------------------------------------------: |
 | [`en_core_web_trf`](/models/en#en_core_web_trf) (spaCy v3) |   95.5 |   98.3 | 89.7 |                                                                  1k |                                                                 8k |
-| [`en_core_web_lg`](/models/en#en_core_web_lg) (spaCy v3)   |   92.2 |   97.4 | 85.8 |                                                                  7k |                                                                    |
+| [`en_core_web_lg`](/models/en#en_core_web_lg) (spaCy v3)   |   92.2 |   97.4 | 85.4 |                                                                  7k |                                                                    |
-| `en_core_web_lg` (spaCy v2)                                |   91.9 |   97.2 |      |                                                                 10k |                                                                    |
+| `en_core_web_lg` (spaCy v2)                                |   91.9 |   97.2 | 85.7 |                                                                 10k |                                                                    |
 
 <figcaption class="caption">
 
 **Full pipeline accuracy and speed** on the
-[OntoNotes 5.0](https://catalog.ldc.upenn.edu/LDC2013T19) corpus.
+[OntoNotes 5.0](https://catalog.ldc.upenn.edu/LDC2013T19) corpus (reported on
+the development set).
 
 </figcaption>
 

website/docs/usage/facts-figures.md

@@ -10,6 +10,18 @@ menu:
 
 ## Comparison {#comparison hidden="true"}
 
+spaCy is a **free, open-source library** for advanced **Natural Language
+Processing** (NLP) in Python. It's designed specifically for **production use**
+and helps you build applications that process and "understand" large volumes of
+text. It can be used to build information extraction or natural language
+understanding systems.
+
+### Feature overview {#comparison-features}
+
+import Features from 'widgets/features.js'
+
+<Features />
+
 ### When should I use spaCy? {#comparison-usage}
 
 - ✅ **I'm a beginner and just getting started with NLP.** – spaCy makes it easy

website/src/widgets/features.js

@@ -0,0 +1,72 @@
+import React from 'react'
+import { graphql, StaticQuery } from 'gatsby'
+
+import { Ul, Li } from '../components/list'
+
+export default () => (
+    <StaticQuery
+        query={query}
+        render={({ site }) => {
+            const { counts } = site.siteMetadata
+            return (
+                <Ul>
+                    <Li>
+                        ✅ Support for <strong>{counts.langs}+ languages</strong>
+                    </Li>
+                    <Li>
+                        ✅ <strong>{counts.models} trained pipelines</strong> for{' '}
+                        {counts.modelLangs} languages
+                    </Li>
+                    <Li>
+                        ✅ Multi-task learning with pretrained <strong>transformers</strong> like
+                        BERT
+                    </Li>
+                    <Li>
+                        ✅ Pretrained <strong>word vectors</strong>
+                    </Li>
+                    <Li>✅ State-of-the-art speed</Li>
+                    <Li>
+                        ✅ Production-ready <strong>training system</strong>
+                    </Li>
+                    <Li>
+                        ✅ Linguistically-motivated <strong>tokenization</strong>
+                    </Li>
+                    <Li>
+                        ✅ Components for <strong>named entity</strong> recognition, part-of-speech
+                        tagging, dependency parsing, sentence segmentation,{' '}
+                        <strong>text classification</strong>, lemmatization, morphological analysis,
+                        entity linking and more
+                    </Li>
+                    <Li>
+                        ✅ Easily extensible with <strong>custom components</strong> and attributes
+                    </Li>
+                    <Li>
+                        ✅ Support for custom models in <strong>PyTorch</strong>,{' '}
+                        <strong>TensorFlow</strong> and other frameworks
+                    </Li>
+                    <Li>
+                        ✅ Built in <strong>visualizers</strong> for syntax and NER
+                    </Li>
+                    <Li>
+                        ✅ Easy <strong>model packaging</strong>, deployment and workflow management
+                    </Li>
+                    <Li>✅ Robust, rigorously evaluated accuracy</Li>
+                </Ul>
+            )
+        }}
+    />
+)
+
+const query = graphql`
+    query FeaturesQuery {
+        site {
+            siteMetadata {
+                counts {
+                    langs
+                    modelLangs
+                    models
+                }
+            }
+        }
+    }
+`

website/src/widgets/landing.js

@@ -14,13 +14,13 @@ import {
     LandingBanner,
 } from '../components/landing'
 import { H2 } from '../components/typography'
-import { Ul, Li } from '../components/list'
 import { InlineCode } from '../components/code'
 import Button from '../components/button'
 import Link from '../components/link'
 
 import QuickstartTraining from './quickstart-training'
 import Project from './project'
+import Features from './features'
 import courseImage from '../../docs/images/course.jpg'
 import prodigyImage from '../../docs/images/prodigy_overview.jpg'
 import projectsImage from '../../docs/images/projects.png'
@@ -56,7 +56,7 @@ for entity in doc.ents:
 }
 
 const Landing = ({ data }) => {
-    const { counts, nightly } = data
+    const { nightly } = data
     const codeExample = getCodeExample(nightly)
     return (
         <>
@@ -98,51 +98,7 @@ const Landing = ({ data }) => {
 
                 <LandingCol>
                     <H2>Features</H2>
-                    <Ul>
+                    <Features />
-                        <Li>
-                            ✅ Support for <strong>{counts.langs}+ languages</strong>
-                        </Li>
-                        <Li>
-                            ✅ <strong>{counts.models} trained pipelines</strong> for{' '}
-                            {counts.modelLangs} languages
-                        </Li>
-                        <Li>
-                            ✅ Multi-task learning with pretrained <strong>transformers</strong>{' '}
-                            like BERT
-                        </Li>
-                        <Li>
-                            ✅ Pretrained <strong>word vectors</strong>
-                        </Li>
-                        <Li>✅ State-of-the-art speed</Li>
-                        <Li>
-                            ✅ Production-ready <strong>training system</strong>
-                        </Li>
-                        <Li>
-                            ✅ Linguistically-motivated <strong>tokenization</strong>
-                        </Li>
-                        <Li>
-                            ✅ Components for <strong>named entity</strong> recognition,
-                            part-of-speech tagging, dependency parsing, sentence segmentation,{' '}
-                            <strong>text classification</strong>, lemmatization, morphological
-                            analysis, entity linking and more
-                        </Li>
-                        <Li>
-                            ✅ Easily extensible with <strong>custom components</strong> and
-                            attributes
-                        </Li>
-                        <Li>
-                            ✅ Support for custom models in <strong>PyTorch</strong>,{' '}
-                            <strong>TensorFlow</strong> and other frameworks
-                        </Li>
-                        <Li>
-                            ✅ Built in <strong>visualizers</strong> for syntax and NER
-                        </Li>
-                        <Li>
-                            ✅ Easy <strong>model packaging</strong>, deployment and workflow
-                            management
-                        </Li>
-                        <Li>✅ Robust, rigorously evaluated accuracy</Li>
-                    </Ul>
                 </LandingCol>
             </LandingGrid>
 
@@ -333,11 +289,6 @@ const landingQuery = graphql`
             siteMetadata {
                 nightly
                 repo
-                counts {
-                    langs
-                    modelLangs
-                    models
-                }
             }
         }
     }