@prefix dc: . @prefix this: . @prefix sub: . @prefix xsd: . @prefix prov: . @prefix pav: . @prefix np: . @prefix linkflows: . sub:Head { this: np:hasAssertion sub:assertion; np:hasProvenance sub:provenance; np:hasPublicationInfo sub:pubinfo; a np:Nanopublication . } sub:assertion { sub:comment-3 a linkflows:ActionNeededComment, linkflows:ContentComment, linkflows:NegativeComment, linkflows:ReviewComment; linkflows:hasCommentText "* From my perspective, the aspect of joint T-Box and A-Box population is somewhat overstated. Certainly, FactExtractor is capable of populating both T-Box and A-Box _simultaneously_, i.e., relying on one and the same pipeline of analyis. However, I cannot see any aspect in the system that indicates a genuinely _joint_ approach in the sense that T-Box and A-Box knowledge acquisition is closely intertwined in order to exploit mutual dependencies between the two (which would correspond to the common use of the term in the machine learning or NLP literature). I would suggest to change the terminology here."; linkflows:hasImpact "3"^^xsd:positiveInteger; linkflows:refersTo . } sub:provenance { sub:assertion prov:hadPrimarySource ; prov:wasAttributedTo . } sub:pubinfo { this: dc:created "2019-11-26T09:05:11+01:00"^^xsd:dateTime; pav:createdBy . }