31:T43c,md`[WinkNLP](https://github.com/winkjs/wink-nlp) is designed to work on Node.js and web browsers both. Apart from building a server side solution using Node.js, you can build a pure browser side NLP app with equal ease. To create Observable notebooks, import required packages using tools like [Skypack](https://www.skypack.dev/) or [unpkg](https://unpkg.com/), as outlined in the section on **Setup** towards the end. With "nlp" and "its/as" helpers handy, you are all set to perform natural language processing. This notebook has two examples, viz. **(a)** detecting named entities and subsequently highlighting them in the text via the [**.markup()**](https://winkjs.org/wink-nlp/visualizing-markup.html) api, and **(b)** building frequency table of token types using [**as.freqTable**](https://winkjs.org/wink-nlp/its-as-helper.html) helper. With [winkNLP's](https://github.com/winkjs/wink-nlp) [**built-in visualization APIs**](https://winkjs.org/wink-nlp/markup.html), it is possible to create beautiful text visualizations on Observable using [d3.js](https://d3js.org/).`32:[] 2f:{"title":"How to run wink-nlp on Observable?","cells":[{"id":156,"value":"md`# How to run wink-nlp on Observable?`","pinned":false,"hidden":false,"mode":"ojs"},{"id":302,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":245,"value":"md`### Sample Text to be processed`","pinned":false,"hidden":false,"mode":"ojs"},{"id":233,"value":"text = 'Its quarterly profits jumped 76% to $1.13 billion for the three months to December.';","pinned":false,"hidden":false,"mode":"ojs"},{"id":249,"value":"md`### Perform NLP on the Sample Text`","pinned":false,"hidden":false,"mode":"ojs"},{"id":255,"value":"doc = nlp.readDoc( text );","pinned":true,"hidden":false,"mode":"ojs"},{"id":263,"value":"md`### Highlight Entities`","pinned":false,"hidden":false,"mode":"ojs"},{"id":202,"value":"{\n // Markup each entity.\n doc.entities()\n .each((e) => e.markup('', `_{[${e.out(its.detail).type}]}`));\n // Return as HTML.\n return html`

${doc.out(its.markedUpText)}

`;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":266,"value":"md`### Build Frequency Table of Token Types`","pinned":false,"hidden":false,"mode":"ojs"},{"id":204,"value":"{\n let table = '';\n doc.tokens()\n .out(its.type, as.freqTable)\n .forEach((e) => {table+=``;})\n return html`${table}

Word	Frequency
${e[0]}	${e[1]}

`; \n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":288,"value":"md`---`","pinned":false,"hidden":false,"mode":"ojs"},{"id":280,"value":"md`### Setup`","pinned":false,"hidden":false,"mode":"ojs"},{"id":209,"value":"md`#### 1. Import [winkNLP](https://github.com/winkjs/wink-nlp)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":216,"value":"winkNLP = (await import('https://cdn.skypack.dev/wink-nlp')).default;","pinned":true,"hidden":false,"mode":"ojs"},{"id":219,"value":"md`#### 2. Import [Wink English Lite Web Model](https://github.com/winkjs/wink-eng-lite-web-model)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":222,"value":"model = (await import('https://cdn.skypack.dev/wink-eng-lite-web-model')).default;","pinned":true,"hidden":false,"mode":"ojs"},{"id":225,"value":"md`#### 3. Instantiate wink-nlp using model`","pinned":false,"hidden":false,"mode":"ojs"},{"id":230,"value":"nlp = winkNLP( model );","pinned":true,"hidden":false,"mode":"ojs"},{"id":237,"value":"md`#### 4. Acquire [\"its\" and \"as\" helpers](https://winkjs.org/wink-nlp/its-as-helper.html)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":240,"value":"its = nlp.its;","pinned":true,"hidden":false,"mode":"ojs"},{"id":241,"value":"as = nlp.as;","pinned":true,"hidden":false,"mode":"ojs"},{"id":343,"value":"md`---`","pinned":false,"hidden":false,"mode":"ojs"},{"id":346,"value":"md`### Styles`","pinned":false,"hidden":false,"mode":"ojs"},{"id":353,"value":"html`\n \n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":400,"value":"md`---\n### About\n[**WinkNLP**](https://winkjs.org/) is a **developer friendly** JavaScript library for Natural Language Processing (NLP). Designed specifically to make development of NLP solutions **easier** and **faster**, winkNLP is optimized for the right balance of performance and accuracy. The package can handle large amount of raw text at speeds **over 525,000 tokens/second** for the entire NLP pipeline. And with a **test coverage of ~100%**, [wink-nlp](https://winkjs.org/) is a tool for building production grade systems with confidence.`","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W32","stdlib":"1","titling":"auto"}