Nanopublications

@prefix dc: <http://purl.org/dc/terms/> .
@prefix this: <http://purl.org/np/RA8af3xefwEX8Clp1KSma1B8Y6Yk98rC1eOgWMZBp6DhQ> .
@prefix sub: <http://purl.org/np/RA8af3xefwEX8Clp1KSma1B8Y6Yk98rC1eOgWMZBp6DhQ#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix prov: <http://www.w3.org/ns/prov#> .
@prefix pav: <http://purl.org/pav/> .
@prefix np: <http://www.nanopub.org/nschema#> .
@prefix doco: <http://purl.org/spar/doco/> .
@prefix c4o: <http://purl.org/spar/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: <http://it.dbpedia.org/resource/> .
@prefix dbpo: <http://dbpedia.org/ontology/> .
@prefix fact: <http://fact.extraction.org/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
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 <http://dx.doi.org/10.3233/SW-170269> ;
prov:wasAttributedTo <https://orcid.org/0000-0002-5456-7964> .
}

sub:pubinfo {
this: dc:created "2019-11-10T18:05:11+01:00"^^xsd:dateTime ;
pav:createdBy <https://orcid.org/0000-0002-7114-6459> .
}