@prefix dc: .
@prefix this: .
@prefix sub: .
@prefix xsd: .
@prefix prov: .
@prefix pav: .
@prefix np: .
@prefix doco: .
@prefix c4o: .
sub:Head {
this: np:hasAssertion sub:assertion;
np:hasProvenance sub:provenance;
np:hasPublicationInfo sub:pubinfo;
a np:Nanopublication .
}
sub:assertion {
sub:paragraph c4o:hasContent """The FACT EXTRACTOR is a full-fledged Information Extraction NLP pipeline that analyses a natural language textual corpus and generates structured machine-readable assertions. Such assertions are disambiguated by linking text fragments to entity URIs of the target KB, namely DBpedia, and are assigned a confidence score. For instance, given the sentence Buffon plays for Serie A club Juventus since 2001, our system produces the following dataset:
@prefix dbpedia: .
@prefix dbpo: .
@prefix fact: .
@prefix xsd: .
dbpedia:Gianluigi_Buffon dbpo:careerStation dbpedia:CareerStation_01 .
dbpedia:CareerStation_01
dbpo:team dbpedia:Juventus_Football_Club ;
fact:competition dbpedia:Serie_A ;
dbpo:startYear \"2001\"^^xsd:gYear ;
fact:confidence \"0.906549\"^^xsd:float .""";
a doco:Paragraph .
}
sub:provenance {
sub:assertion prov:hadPrimarySource ;
prov:wasAttributedTo .
}
sub:pubinfo {
this: dc:created "2019-11-10T18:05:11+01:00"^^xsd:dateTime;
pav:createdBy .
}