A number of graph-based semantic representation frameworks have emerged in recent years, but there are few parallel annotated corpora across them. We want to explore the viability of transforming graphs from one framework into another to construct parallel datasets. In this work, we consider graph rewriting from Discourse Representation Structures (Parallel Meaning Bank (PMB) variant) to Abstract Meaning Representation (AMR). We first build a gold AMR corpus of 102 sentences from the PMB. We then construct a rule base, aided by a further 95 sentences. No benchmark for this task exists, so we compare our system's output to that of state-of-the-art AMR parsers, and explore the more challenging cases. Finally, we discuss where the two frameworks diverge in encoding semantic phenomena.