KBpedia Knowledge Structure
 
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Reference Concepts
 
 

 
 
 

Core Structure

These are the structural linkages among the core knowledge bases for this RC: ... more

The core structure for KBpedia is derived from six (6) main knowledge bases — OpenCyc, UMBEL, GeoNames, DBpedia, Wikipedia and Wikidata. The conceptual relationships in the KBpedia Knowledge Ontology (KKO) are largely drawn from OpenCyc and UMBEL, though any of the other four sources may contribute local knowledge graph structure. Additional reference concepts (RCs) are contributed primarily from GeoNames and Wikipedia. Wikidata contributes the bulk of the instance data, though instance records are actually drawn from all sources. DBpedia and Wikidata are also the primary sources for attribute characterizations of the instances. Two characteristics define what is a core contributor to the KBpedia structure: 1) the scale and completeness of the source; and 2) its contribution of a large number of RCs to the overall KKO knowledge graph. The KBs in the core structure play a central role in the scope and definition of KBpedia. This core structure of KBpedia is supplemented by mappings to about 20 additional external linkages, which are highly useful for interoperability purposes, but do not themselves contribute to the same extent to the RC scope of the KKO graph. Instances (or entities) are related to the KKO graph via the rdfs:type predicate, which assigns an entity to one or more parental classes. RCs within the KKO graph may be equivalent (owl:equivalentClass), a parent super class (kko:superClassOf), a child sub class (rdfs:subClassOf), or a closely related concept (kko:isCloselyRelated). These relationships define the edges between the nodes in the graph structure, and are also the basis for logical inferencing.

Sub-Classes
Super-Classes
Equivalent Classes
Same As
 
 
 

Entities

Here are some entities for this reference concept: ... more

Entities are distinct, nameable, individual things. Entities may be physical objects or conceptual works or discrete ideas, so long as they may be characterized by attributes shared by other instances. Entities may be parts of other things, so long as they have a distinct identity and character. Entities with shared attributes that are the essence of the things may be grouped into natural types, called entity types. These entity types may be further related to other entity types in natural groupings or hierarchies depending on the attributes and their essences that are shared among them. For the current RC, which is by definition an entity type, we are displaying a small portion of its entities. You can browse all entities for this RC by clicking the Browse all entities button.

Number of entities
Entity examples
 
 
 

Aspect-related Entities

 
 
 

Typologies

The concept is a member of these typologies: ... more

About 3/4 of all of the reference concepts (RCs) in KBpedia represent classes of entities, which themselves are organized into about 30 typologies. Most of these typologies are disjoint (lack overlap) from one another, which provides an efficient mechanism for testing subsets and filtering entities into smaller groups for computational purposes. The major groupings of types reside in core typologies, which is where the largest degree of disjointedness occurs. There are some upper typologies (such as Living Things over Plants, Animals, etc.) that are used mostly for organizational purposes. The core typologies are the key ones to focus upon for distinguishing large groupings of entities.

 
 
 

Connected Worlds

The concept lives in these external knowledge graphs: ... more

KBpedia reference concepts are explicitly mapped to major external sources (Wikidata, Wikipedia, DBpedia, schema.org, GeoNames) and a curated set of boutique ontologies (Dublin Core, FOAF, Transit, etc.). These connections act as bridges to the broader Web of Data. Equivalent classes represent direct matches; narrower/broader show hierarchical alignments. Boutique mappings — though rare — are always shown first because of their specialized value.

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KBpedia exploits large-scale knowledge bases and semantic technologies for machine learning, data interoperability and mapping, and fact extraction and tagging.

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