However, recently the reverse process, i.e. the generation of texts from AMRs, has started to receive scholarly attention (Flanigan et al., 2016; Song et al., 2016; <cite>Pourdamghani et al., 2016</cite>; Song et al., 2017; Konstas et al., 2017) . We assume that in practical applications, conceptualisation models or dialogue managers (models which decide "what to say") output AMRs. In this paper we study different ways in which these AMRs can be converted into natural language (deciding "how to say it").