About https://w3id.org/scholarlydata/inproceedings/www2012/paper/1290

Subject: https://w3id.org/scholarlydata/inproceedings/www2012/paper/1290Property: http://www.w3.org/1999/02/22-rdf-syntax-ns#typehttp://www.w3.org/2002/07/owl#Thinghttp://purl.org/spar/fabio/ProceedingsPaperhttps://w3id.org/scholarlydata/ontology/conference-ontology.owl#InProceedingshttp://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#ObjectProperty: http://www.w3.org/2000/01/rdf-schema#labelSPARQL Template Based Question AnsweringProperty: http://www.w3.org/2002/07/owl#sameAshttp://data.semanticweb.org/conference/www/2012/paper/1290Property: http://swrc.ontoware.org/ontology#abstractQuestion answering (QA) systems provide a user-friendly way to obtain information from data sources. In particular, the generation of SPARQL queries on a particular RDF knowledge base from natural language queries has gained momentum, since they only require minimal user effort. However, none of the currently existing QA system can reliably generate such queries over large and heterogeneous knowledge base, which we can commonly find in the web of data. In this paper, we propose an approach, which is based on generating templates from natural language questions. Those templates are instantiated to form a set of SPARQL queries, which are then tested using several optimisations. We show the feasibility of the approach by successfully applying it on an existing QA benchmark.Property: http://purl.org/dc/elements/1.1/creatorhttps://w3id.org/scholarlydata/person/daniel-gerberhttps://w3id.org/scholarlydata/person/philipp-cimianohttps://w3id.org/scholarlydata/person/axel-cyrille-ngonga-ngomohttps://w3id.org/scholarlydata/person/jens-lehmannhttps://w3id.org/scholarlydata/person/lorenz-buehmannhttps://w3id.org/scholarlydata/person/christina-ungerProperty: http://purl.org/dc/elements/1.1/subjectQuestion AnsweringSPARQLSemantic WebNatural-Language PatternsProperty: http://purl.org/dc/elements/1.1/titleSPARQL Template Based Question AnsweringProperty: http://purl.org/ontology/bibo/authorListhttps://w3id.org/scholarlydata/inproceedings/www2012/paper/1290/authorListProperty: http://xmlns.com/foaf/0.1/makerhttps://w3id.org/scholarlydata/person/daniel-gerberhttps://w3id.org/scholarlydata/person/lorenz-buehmannhttps://w3id.org/scholarlydata/person/christina-ungerhttps://w3id.org/scholarlydata/person/jens-lehmannhttps://w3id.org/scholarlydata/person/philipp-cimianohttps://w3id.org/scholarlydata/person/axel-cyrille-ngonga-ngomoProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#abstractQuestion answering (QA) systems provide a user-friendly way to obtain information from data sources. In particular, the generation of SPARQL queries on a particular RDF knowledge base from natural language queries has gained momentum, since they only require minimal user effort. However, none of the currently existing QA system can reliably generate such queries over large and heterogeneous knowledge base, which we can commonly find in the web of data. In this paper, we propose an approach, which is based on generating templates from natural language questions. Those templates are instantiated to form a set of SPARQL queries, which are then tested using several optimisations. We show the feasibility of the approach by successfully applying it on an existing QA benchmark.Property: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#hasAuthorListhttps://w3id.org/scholarlydata/inproceedings/www2012/paper/1290/authorListProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#isPartOfhttps://w3id.org/scholarlydata/conference/www/2012/proceedingsProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#keywordNatural-Language PatternsQuestion AnsweringSPARQLSemantic WebProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#titleSPARQL Template Based Question Answering
Subject: https://w3id.org/scholarlydata/person/axel-cyrille-ngonga-ngomoProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/www2012/paper/1290
Subject: https://w3id.org/scholarlydata/person/daniel-gerberProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/www2012/paper/1290
Subject: https://w3id.org/scholarlydata/person/jens-lehmannProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/www2012/paper/1290
Subject: https://w3id.org/scholarlydata/person/lorenz-buehmannProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/www2012/paper/1290
Subject: https://w3id.org/scholarlydata/person/philipp-cimianoProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/www2012/paper/1290
Subject: https://w3id.org/scholarlydata/person/christina-ungerProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/www2012/paper/1290
Subject: https://w3id.org/scholarlydata/conference/www/2012/proceedingsProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#hasParthttps://w3id.org/scholarlydata/inproceedings/www2012/paper/1290