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I am looking for a dataset containing articles (with article-text, or alternatively I am fine with only URLs too) and the corresponding topic label (i.e. politics, art, gardening etc.) Any idea?

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The News category dataset seems to fit your description.

This dataset contains around 200k news headlines from the year 2012 to 2018 obtained from HuffPost. The model trained on this dataset could be used to identify tags for untracked news articles or to identify the type of language used in different news articles. Each news headline has a corresponding category (politics, entertainment, travel, etc.)

Alternatively, you can use:

Reuters Text Categorization Dataset:

This dataset contains 21,578 Reuters documents that appeared on Reuters newswire in 1987. The dataset is split into a training set of 13,625, and a testing set of 6,188. Each document is tagged according to date, topic, place, people, organizations, companies, and etc.

The 20 Newsgroups Dataset:

The 20 Newsgroups Dataset is a popular dataset for experimenting with text applications of machine learning techniques, including text classification. The dataset collates approximately 20,000 newsgroup documents partitioned across 20 different newsgroups, each corresponding to a different topic. The website offers three versions of the dataset for slightly different purposes.

You can refer to this link for more.

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