DeveloperOats/DBPedia_Classes

1---2annotations_creators: []3language:4- en5language_creators: []6license:7- cc0-1.08multilinguality:9- monolingual10pretty_name: 'DBpedia'11size_categories:12- 1M<n<10M13source_datasets: []14tags: []15task_categories:16- text-classification17task_ids:18- topic-classification19---20 21About Dataset22 23DBpedia (from "DB" for "database") is a project aiming to extract structured content from the information created in Wikipedia.24This 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.25A 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.26 27This is an excellent benchmark for hierarchical multiclass/multilabel text classification.28Some example approaches are included as code snippets.29Content30 31DBPedia dataset with multiple levels of hierarchy/classes, as a multiclass dataset.32Original DBPedia ontology (triplets data): https://wiki.dbpedia.org/develop/datasets33Listing of the class tree/taxonomy: http://mappings.dbpedia.org/server/ontology/classes/34Acknowledgements35 36Thanks to the Wikimedia foundation for creating Wikipedia, DBPedia and associated open-data goodness!37 38Thanks to my colleagues at Sparkbeyond (https://www.sparkbeyond.com) for pointing me towards the taxonomical version of this dataset (as opposed to the classic 14 class version)39Inspiration40 41    Try different NLP models.42    See also https://www.kaggle.com/datasets/danofer/dbpedia-classes43    Compare to the SOTA in Text Classification on DBpedia - https://paperswithcode.com/sota/text-classification-on-dbpedia