@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix orcid: <https://orcid.org/> .
@prefix this: <http://purl.org/np/RAhEjruJgVM6tLGku_gnXctO7D0ZgMeXUN2T9FDhChFcY> .
@prefix sub: <http://purl.org/np/RAhEjruJgVM6tLGku_gnXctO7D0ZgMeXUN2T9FDhChFcY#> .
@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 "In scenarios in which crowdsourcing is applied to validate the results of machine computation tasks, question filtering relies on specific thresholds or historical information about the likelihood that human in- put will significantly improve the results generated algorithmically. Find-Fix-Verify addresses tasks that initially can be very complex (or very large), like in our case the discovery and classification of various types of errors in DBpedia.";
    a doco:Paragraph .
}

sub:provenance {
  sub:assertion prov:hadPrimarySource <http://dx.doi.org/10.3233/SW-160239>;
    prov:wasAttributedTo orcid:0000-0003-0530-4305 .
}

sub:pubinfo {
  this: dcterms:created "2019-11-07T12:47:11+01:00"^^xsd:dateTime;
    pav:createdBy orcid:0000-0002-7114-6459 .
}