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fix(README): correct table column width
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README.md

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@@ -30,7 +30,7 @@ WinkNLP can easily process large amount of raw text at speeds over <mark>**650,0
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WinkNLP has a [comprehensive natural language processing (NLP) pipeline](https://winkjs.org/wink-nlp/processing-pipeline.html) covering tokenization, sentence boundary detection (sbd), negation handling, sentiment analysis, part-of-speech (pos) tagging, named entity recognition (ner), custom entities recognition (cer). It offers a rich feature set:
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<table>
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<tr><td style="width:45%">Fast, lossless & multilingual tokenizer ⚡️</td><td>For example, a multilingual text string <b><code style="font-size: 0.9em">"¡Hola! नमस्कार! Hi! Bonjour chéri"</code></b> tokenizes as <code style="font-size: 0.9em">["¡", "Hola", "!", "नमस्कार", "!", "Hi", "!", "Bonjour", "chéri"]</code>. It tokenizes text at <b>4 million</b> tokens/second on a M1 MBP's browser.</td></tr>
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<tr><td width="330px;">Fast, lossless & multilingual tokenizer ⚡️</td><td>For example, the text string <b><code style="font-size: 0.9em">"¡Hola! नमस्कार! Hi! Bonjour chéri"</code></b> tokenizes as <code style="font-size: 0.9em">["¡", "Hola", "!", "नमस्कार", "!", "Hi", "!", "Bonjour", "chéri"]</code>. It tokenizes text at <b>4 million</b> tokens/second on a M1 MBP's browser.</td></tr>
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<tr><td>Developer friendly and intuitive <a href="https://winkjs.org/wink-nlp/getting-started.html">API</a> 💚</td><td>As simple as DOM manipulation; most <a href="https://observablehq.com/@winkjs/how-to-build-a-naive-wikification-tool?collection=@winkjs/winknlp-recipes">live examples</a> have <b>30-40</b> lines of code.</td></tr>
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<tr><td>Best-in-class <a href="https://winkjs.org/wink-nlp/visualizing-markup.html">text visualization</a> 🖼</td><td>Programmatically <b><a href="https://winkjs.org/wink-nlp/markup.html">mark</a></b> tokens, sentences, entities, etc. using HTML mark or any other tag of your choice.</td></tr>
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<tr><td>Extensive text processing features ♻️</td><td>Checkout how a <a href="https://github.com/winkjs/wink-naive-bayes-text-classifier#readme">Naive Bayes classifier</a> achieves <b>impressive</b> chatbot intent classification accuracy with right kind of preprocessing with winkNLP.</td></tr>

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