@prefix dc: <http://purl.org/dc/terms/> .
@prefix this: <http://purl.org/np/RAWZJjdcOilpbmMrrTdmvOFucSjwWRxIf4o-5tsI8PRoA> .
@prefix sub: <http://purl.org/np/RAWZJjdcOilpbmMrrTdmvOFucSjwWRxIf4o-5tsI8PRoA#> .
@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-15 a linkflows:ActionNeededComment, linkflows:ContentComment, linkflows:NegativeComment,
      linkflows:ReviewComment;
    linkflows:hasCommentText "The comparison with Legalo is unfair (cf. [8] for more details) In fact, Legalo: * relies on FRED (and its frame-based representation of natural language sentences) for generating binary relations; * works either on Wikipedia articles or generic free text inputs; * can be used for KB enrichment (cf. property matcher in the architecture of Legalo). [8] \"From hyperlinks to Semantic Web properties using Open Knowledge Extraction\". Valentina Presutti, Andrea Giovanni Nuzzolese, Sergio Consoli, Aldo Gangemi, and Diego Reforgiato. Accepted for publication on Semantic Web Journal (http://semantic-web-journal.org/system/files/swj1195.pdf).";
    linkflows:hasImpact "3"^^xsd:positiveInteger;
    linkflows:refersTo <http://purl.org/np/RAe7QzdX1jKDqnhBA0pbe8TMLywibAedB3B0Ps37JQdxM#paragraph> .
}

sub:provenance {
  sub:assertion prov:hadPrimarySource <http://dx.doi.org/10.3233/SW-170269>;
    prov:wasAttributedTo <https://orcid.org/0000-0003-2928-9496> .
}

sub:pubinfo {
  this: dc:created "2019-11-26T09:05:11+01:00"^^xsd:dateTime;
    pav:createdBy <https://orcid.org/0000-0002-7114-6459> .
}