TY - JOUR
T1 - Building up ontologies with property axioms from English wikipedia
AU - Kawakami, Tokio
AU - Morita, Takeshi
AU - Yamaguchi, Takahira
N1 - Publisher Copyright:
© 2020, Japanese Society for Artificial Intelligence. All rights reserved.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - Large-scale ontologies have received much attention in various fields such as information retrieval, data integration, and question answering. However, since it is costly to construct and maintain large-scale ontologies manually, several ontology learning methods from Wikipedia have been proposed. YAGO and DBpedia are famous examples of large-scale ontologies automatically constructed from multilingual Wikipedia. However, there is room to extract from Wikipedia many kinds of relationships that are not included in YAGO or DBpedia. Previously, we proposed a method for constructing large-scale ontologies named Japanese Wikipedia Ontology (JWO) from Japanese Wikipedia. Since JWO has been constructed using several methods that are different from the extracting methods of YAGO and DBpedia, it is possible to extract relationships that do not exist in YAGO or DBpedia by using these methods. However, some of the methods are Japanese language-dependent, and cannot be applied directly to English Wikipedia. In this paper, we propose methods for constructing large-scale ontologies named English Wikipedia Ontology (EWO) from English Wikipedia. To achieve this, we have modified the Japanese language-dependent methods of JWO and extended several methods for extracting property axioms. EWO includes Is-a relations (rdfs:subClassOf), classinstance relations (rdf:type), property relations and types, and synonyms (owl:sameAs). The property relations are triples: property domain (rdfs:domain), property range (rdfs:range), and property hypernymy-hyponymy relations (rdfs:subPropertyOf). The property types are object (owl:ObjectProperty), data (owl:DatatypeProperty), symmetric (owl:SymmetricProperty), transitive (owl:TransitiveProperty), functional (owl:FunctionalProperty), inverse functional (owl:InverseFunctionalProperty), asymmetric (owl:AsymmetricProperty), reflexive (owl:ReflexiveProperty) and irreflexive (owl:IrreflexiveProperty). To evaluate EWO, we compared it with existing ontologies constructed from English Wikipedia. Thus, we clarified the differences between the existing ontologies and EWO.
AB - Large-scale ontologies have received much attention in various fields such as information retrieval, data integration, and question answering. However, since it is costly to construct and maintain large-scale ontologies manually, several ontology learning methods from Wikipedia have been proposed. YAGO and DBpedia are famous examples of large-scale ontologies automatically constructed from multilingual Wikipedia. However, there is room to extract from Wikipedia many kinds of relationships that are not included in YAGO or DBpedia. Previously, we proposed a method for constructing large-scale ontologies named Japanese Wikipedia Ontology (JWO) from Japanese Wikipedia. Since JWO has been constructed using several methods that are different from the extracting methods of YAGO and DBpedia, it is possible to extract relationships that do not exist in YAGO or DBpedia by using these methods. However, some of the methods are Japanese language-dependent, and cannot be applied directly to English Wikipedia. In this paper, we propose methods for constructing large-scale ontologies named English Wikipedia Ontology (EWO) from English Wikipedia. To achieve this, we have modified the Japanese language-dependent methods of JWO and extended several methods for extracting property axioms. EWO includes Is-a relations (rdfs:subClassOf), classinstance relations (rdf:type), property relations and types, and synonyms (owl:sameAs). The property relations are triples: property domain (rdfs:domain), property range (rdfs:range), and property hypernymy-hyponymy relations (rdfs:subPropertyOf). The property types are object (owl:ObjectProperty), data (owl:DatatypeProperty), symmetric (owl:SymmetricProperty), transitive (owl:TransitiveProperty), functional (owl:FunctionalProperty), inverse functional (owl:InverseFunctionalProperty), asymmetric (owl:AsymmetricProperty), reflexive (owl:ReflexiveProperty) and irreflexive (owl:IrreflexiveProperty). To evaluate EWO, we compared it with existing ontologies constructed from English Wikipedia. Thus, we clarified the differences between the existing ontologies and EWO.
KW - Ontology learning
KW - Property axiom
KW - Semantics
KW - Wikipedia
UR - http://www.scopus.com/inward/record.url?scp=85088207419&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85088207419&partnerID=8YFLogxK
U2 - 10.1527/tjsai.D-J33
DO - 10.1527/tjsai.D-J33
M3 - Article
AN - SCOPUS:85088207419
SN - 1346-0714
VL - 35
SP - 1
EP - 14
JO - Transactions of the Japanese Society for Artificial Intelligence
JF - Transactions of the Japanese Society for Artificial Intelligence
IS - 4
M1 - D-J33
ER -