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DBPEDIA_test.csv → DeveloperOats--DBPedia_Classes/csv-test.parquet

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DBPEDIA_train.csv → DeveloperOats--DBPedia_Classes/csv-train.parquet

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DBPEDIA_val.csv → DeveloperOats--DBPedia_Classes/csv-validation.parquet

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README.md

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----
-annotations_creators: []
-language:
-- en
-language_creators: []
-license:
-- cc0-1.0
-multilinguality:
-- monolingual
-pretty_name: 'DBpedia'
-size_categories:
-- 1M<n<10M
-source_datasets: []
-tags: []
-task_categories:
-- text-classification
-task_ids:
-- topic-classification
----
-
-About Dataset
-
-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/
-Acknowledgements
-
-Thanks to the Wikimedia foundation for creating Wikipedia, DBPedia and associated open-data goodness!
-
-Thanks 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)
-Inspiration
-
-    Try different NLP models.
-    See also https://www.kaggle.com/datasets/danofer/dbpedia-classes
-    Compare to the SOTA in Text Classification on DBpedia - https://paperswithcode.com/sota/text-classification-on-dbpedia