为生命游行：全美反枪支暴力集会在多个城市举行
百度 三门峡空气质量得补金额473万为2月之最 综合PM10、浓度和优良天数这三项河南城市环境空气质量考核因子分析，2月份18省辖市中有9个市在全省省辖市平均值以下，需进行生态支偿，支偿金额由高到低依次是：安阳580万元、南阳175万元、开封170万元、商丘155万元、许昌130万元、平顶山120万元、周口70万元、漯河万元、济源35万元。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.
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External Linkages
The Switzerland concept has these mappings to external knowledge graphs: ... more
KBpedia reference concepts (RCs) are linked to thousands of classes defined in nearly 20 external ontologies used to describe all kinds of public and private datasets. Some of the prominent external vocabularies include schema.org, the major structured data system for search engines, and Dublin Core, a key vocabulary from the library community. Other external vocabularies cover music, organizations, projects, social media, and the like.
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Typologies
The Switzerland 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.
Broader Concepts
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Broader concepts represent the parents (or grandparental lineage in the case of inference) for the current reference concept (RC). The broader concept relationship is expressed using the transitive kko:superClassOf property. This property is the inverse of the rdfs:subClassOf property.
Narrower Concepts
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Narrower concepts represent the children (or grandchild lineages in the case of inference) for the current reference concept (RC). The narrower concept relationship is expressed using the transitive rdfs:subClassOf property. This property is the inverse of the kko:superClassOf property.
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KBpedia |
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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- KBpedia Adds Major eCommerce Capabilities 06/15/2020
- KBpedia Continues Quality Improvements 12/04/2019
- Wikidata Coverage Nearly Complete (98%) 04/08/2019
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