@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 first step involves the creation of the training set: we leverage the crowdsourcing platform CROWDFLOWER 16 and the method described in [18], which requires users to detect the core FEs: these are the fundamental items to distinguish between frames, as opposed to extra ones, thus allowing to automatically induce the correct frame. The training set has a double outcome, as it will feed two classifiers: one will identify FEs, and the other is responsible for frames.";
a doco:Paragraph .
}
sub:provenance {
sub:assertion prov:hadPrimarySource ;
prov:wasAttributedTo .
}
sub:pubinfo {
this: dc:created "2019-11-10T12:34:11+01:00"^^xsd:dateTime;
pav:createdBy .
}