DBpedia Ontology (DBpedia)

The DBpedia ontology is generated from manually curated specifications in the DBpedia Mappings Wiki, providing a structured semantic model extracted from Wikipedia’s rich content across multiple language editions [1] [2]. Each DBpedia release corresponds to a new Wikipedia data extraction, resulting in evolving ontology versions that reflect changes and growth in Wikipedia-based knowledge representation [1].

The DBpedia ontology is a shallow but comprehensive cross-domain ontology developed through community-based mapping and curation activities [1] [2]. It covers diverse knowledge domains including people, organizations, places, creative works, scientific concepts, events, and many other entity types, together with properties that describe relationships between them [1].

DBpedia serves as a bridge between Wikipedia’s semi-structured information and the Semantic Web, enabling linked data publication, knowledge graph construction, information retrieval, entity linking, and semantic data integration [2]. Its ontology and mappings allow Wikipedia-derived information to be represented in RDF and queried using semantic technologies such as SPARQL [2].

Example Usage: Query DBpedia to find relationships between entities, such as all people born in Berlin, all films directed by a specific director, or companies in a particular industry, by using ontology classes such as Person, Film, and Company together with ontology properties that support structured knowledge discovery and data analytics [1] [2].

Metrics & Statistics

Graph Statistics

Total Nodes

18819

Total Edges

32745

Root Nodes

16

Leaf Nodes

14867
Knowledge Coverage Statistics

Classes

790

Individuals

0

Properties

3029
Hierarchical Metrics

Maximum Depth

6

Minimum Depth

0

Average Depth

2.61

Depth Variance

1.66
Breadth Metrics

Maximum Breadth

145

Minimum Breadth

12

Average Breadth

61.57

Breadth Variance

2369.67
LLMs4OL Dataset Statistics

Term Types

0

Taxonomic Relations

799

Non-taxonomic Relations

1665

Average Terms per Type

0.00

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import DBpedia

ontology = DBpedia()
ontology.load("path/to/DBpedia-ontology.owl")

# Extract datasets
data = ontology.extract()

# Access specific relations
term_types = data.term_typings
taxonomic_relations = data.type_taxonomies
non_taxonomic_relations = data.type_non_taxonomic_relations

References