@prefix dc: <http://purl.org/dc/terms/> .
@prefix this: <http://purl.org/np/RANT75p9EbuySUWpX_8nxgBq_JRVCtyfcODFkOcYe7g5Y> .
@prefix sub: <http://purl.org/np/RANT75p9EbuySUWpX_8nxgBq_JRVCtyfcODFkOcYe7g5Y#> .
@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 linkflows: <https://github.com/LaraHack/linkflows_model/blob/master/Linkflows.ttl#> .
sub:Head {
  this: np:hasAssertion sub:assertion ;
    np:hasProvenance sub:provenance ;
    np:hasPublicationInfo sub:pubinfo ;
    a np:Nanopublication .
}
sub:assertion {
  sub:comment-5 a linkflows:ActionNeededComment , linkflows:ContentComment , linkflows:NegativeComment , linkflows:ReviewComment ;
    linkflows:hasCommentText "*I also do not completely understand the \"anatomy\" (weird term) of the crowdsourcing task: The description in Section 7.2.1 and Figure 3 suggest that the sentence to be annotated is presented to the workers together with the frame label. How can this be determined in advance? I suspect that this is done by assuming a fixed mapping between lexical units and a frame, which obviously neglects potential lexical ambiguity at the level of lexical units. This aspect needs clarification, and it should be quantified to what extent such ambiguities really occur and pose a problem to the system." ;
    linkflows:hasImpact "3"^^xsd:positiveInteger ;
    linkflows:refersTo <http://purl.org/nanopub/temp/linkflows/sample-paper-2/v1/f3#figure> , <http://purl.org/np/RAVvOHUZoDh5eHszog4zZdOAlxErkVbZ1Hif2-taGQOFM#section> .
}
sub:provenance {
  sub:assertion prov:hadPrimarySource <http://dx.doi.org/10.3233/SW-170269> ;
    prov:wasAttributedTo <https://orcid.org/0000-0001-6549-066X> .
}
sub:pubinfo {
  this: dc:created "2019-11-26T09:05:11+01:00"^^xsd:dateTime ;
    pav:createdBy <https://orcid.org/0000-0002-7114-6459> .
}