<blockquote>
  <p>There are a lot of datasets for this purpose, <a href="https://arxiv.org/pdf/1502.01710.pdf" rel="nofollow noreferrer">in this paper</a> there
  is detailed Information about the Major ones, I linked in the following:</p>
</blockquote>

<ul>
<li><a href="https://textminingonline.com/tag/dbpedia-ontology-classification-dataset" rel="nofollow noreferrer">DBpediaOntologyClassiﬁcation</a></li>
<li><a href="https://www.kaggle.com/bittlingmayer/amazonreviews" rel="nofollow noreferrer">AmazonReviewSentimentAnalysis</a></li>
<li><a href="https://www.kaggle.com/c/stat-441841-data-challenge-ii/data" rel="nofollow noreferrer">Yahoo! AnswersTopicClassiﬁcation</a></li>
<li><a href="http://www.di.unipi.it/~gulli/AG_corpus_of_news_articles.html" rel="nofollow noreferrer">AG News Categorization in English</a></li>
</ul>
What's the accurate dataset for text classification of tntsearch package
<p>I have found a package for text classification in PHP in which the method for the classifier accepts the sentence and the category like this:</p>

<pre><code>$classifier-&gt;learn('that was a clean election', 'not sports');
$classifier-&gt;learn('that was a nice game','sports');

$classifier-&gt;guess('the game was bad');
// returns sports
</code></pre>

<p>What dataset is best for this approach? 
And also I have a dynamic category which means I can add additional category. My problem is I have to give examples in every category added, which means I need more data in this category.</p>