@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 "In general, most efforts have focused on English, due to the high availability of language resources. Approaches such as [15] explore multilingual directions, by leveraging English as a source and applying statistical machine translation (SMT) for scaling up to target languages. Although the authors claim that their approach do not directly depend on language resources, we argue that SMT still heavily relies on them. Furthermore, all the above efforts concentrate on binary relations, while we generate n-ary ones: under this perspective, EXEMPLAR [10] is a rule-based system which is closely related to ours."; a doco:Paragraph . } sub:provenance { sub:assertion prov:hadPrimarySource ; prov:wasAttributedTo . } sub:pubinfo { this: dc:created "2019-11-10T18:05:11+01:00"^^xsd:dateTime; pav:createdBy . }