DBpedia (from "DB" for "database") is a project aiming to extract structured content from the information created in Wikipedia.
This is an extract of the data (after cleaning, kernel included) that provides taxonomic, hierarchical categories ("classes") for 342,782 wikipedia articles. There are 3 levels,  with 9, 70 and 219 classes respectively.
A version of this dataset is a popular baseline for NLP/text classification tasks. This version of the dataset is much tougher, especially if the L2/L3 levels are used as the targets.

This is an excellent benchmark for hierarchical multiclass/multilabel text classification.
Some example approaches are included as code snippets.

Content

DBPedia dataset with multiple levels of hierarchy/classes, as a multiclass dataset.
Original DBPedia ontology (triplets data): https://wiki.dbpedia.org/develop/datasets
Listing of the class tree/taxonomy: http://mappings.dbpedia.org/server/ontology/classes/