DBPedia Classes
Hierarchical Taxonomy of Wikipedia article classes
@kaggle.danofer_dbpedia_classes
Hierarchical Taxonomy of Wikipedia article classes
@kaggle.danofer_dbpedia_classes
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.
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/
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)
Try different NLP models.
Compare to the SOTA in Text Classification on DBpedia - https://paperswithcode.com/sota/text-classification-on-dbpedia
CREATE TABLE dbpedia_test (
"text" VARCHAR,
"l1" VARCHAR,
"l2" VARCHAR,
"l3" VARCHAR
);CREATE TABLE dbpedia_train (
"text" VARCHAR,
"l1" VARCHAR,
"l2" VARCHAR,
"l3" VARCHAR
);CREATE TABLE dbpedia_val (
"text" VARCHAR,
"l1" VARCHAR,
"l2" VARCHAR,
"l3" VARCHAR
);CREATE TABLE dbp_wiki_data (
"text" VARCHAR,
"l1" VARCHAR,
"l2" VARCHAR,
"l3" VARCHAR,
"wiki_name" VARCHAR,
"word_count" BIGINT
);Anyone who has the link will be able to view this.