About https://w3id.org/scholarlydata/inproceedings/iswc-2019-resource-247

Subject: https://w3id.org/scholarlydata/inproceedings/iswc-2019-resource-247Property: http://www.w3.org/1999/02/22-rdf-syntax-ns#typehttps://w3id.org/scholarlydata/ontology/conference-ontology.owl#InProceedingshttp://www.w3.org/2002/07/owl#Thinghttp://www.ontologydesignpatterns.org/ont/dul/DUL.owl#SocialObjecthttp://www.w3.org/2000/01/rdf-schema#Resourcehttp://www.ontologydesignpatterns.org/ont/dul/DUL.owl#InformationObjecthttp://www.ontologydesignpatterns.org/ont/dul/DUL.owl#Objecthttp://purl.org/spar/fabio/ProceedingsPaperProperty: http://www.w3.org/2000/01/rdf-schema#labelLC-QuAD 2.0: A large dataset for complex question answering over Wikidata and DBpedia .Property: http://swrc.ontoware.org/ontology#abstractProviding machines with the capability of exploring knowledge graphs and answering user questions have been an active area of research in the last decade. Question Answering over knowledge graphs by translating natural language questions to formal queries has been one of the key approaches. To advance the research area several datasets like WebQuestions, QALD and LCQuAD have been published in the past. The biggest data set available for the complex questions (LCQuAD) over the knowledge graph contains five thousand questions. We now provide LC-QuAD 2.0 (Large-Scale Complex Question Answering Dataset) with 30,000 questions, their paraphrases and their corresponding SPARQL queries. LC-QuAD 2.0 is compatible with both Wikidata and DBpedia 2018 knowledge graphs. In this article, we attempt to explain our approach of how the dataset was created and the variety of questions available with examples. We further provide a statistical analysis of the dataset.Property: http://purl.org/dc/elements/1.1/creatorhttps://w3id.org/scholarlydata/person/mohnish-dubeyhttps://w3id.org/scholarlydata/person/debayan-banerjeehttps://w3id.org/scholarlydata/person/jens-lehmannhttps://w3id.org/scholarlydata/person/abdelrahman-abdelkawiProperty: http://purl.org/dc/elements/1.1/subjectDataset Question Answering DBpedia WikidataProperty: http://purl.org/dc/elements/1.1/titleLC-QuAD 2.0: A large dataset for complex question answering over Wikidata and DBpedia .Property: http://purl.org/ontology/bibo/authorListhttps://w3id.org/scholarlydata/authorlist/iswc-2019-resource-247Property: http://xmlns.com/foaf/0.1/makerhttps://w3id.org/scholarlydata/person/mohnish-dubeyhttps://w3id.org/scholarlydata/person/jens-lehmannhttps://w3id.org/scholarlydata/person/debayan-banerjeehttps://w3id.org/scholarlydata/person/abdelrahman-abdelkawiProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#abstractProviding machines with the capability of exploring knowledge graphs and answering user questions have been an active area of research in the last decade. Question Answering over knowledge graphs by translating natural language questions to formal queries has been one of the key approaches. To advance the research area several datasets like WebQuestions, QALD and LCQuAD have been published in the past. The biggest data set available for the complex questions (LCQuAD) over the knowledge graph contains five thousand questions. We now provide LC-QuAD 2.0 (Large-Scale Complex Question Answering Dataset) with 30,000 questions, their paraphrases and their corresponding SPARQL queries. LC-QuAD 2.0 is compatible with both Wikidata and DBpedia 2018 knowledge graphs. In this article, we attempt to explain our approach of how the dataset was created and the variety of questions available with examples. We further provide a statistical analysis of the dataset.Property: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#hasAuthorListhttps://w3id.org/scholarlydata/authorlist/iswc-2019-resource-247Property: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#isPartOfhttps://w3id.org/scholarlydata/conference/iswc/2019/proceedingsProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#keywordDataset Question Answering DBpedia WikidataProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#titleLC-QuAD 2.0: A large dataset for complex question answering over Wikidata and DBpedia .Property: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#relatesToEventhttps://w3id.org/scholarlydata/talk/iswc-2019-resource-247
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