In this paper we present three methods to handle reentrancy for AMR parsing. The first two methods are based on the previous work described above, while the third is a new, more principled method. These methods are applied on the model that reported the best results in the literature, the character-level neural semantic parsing method of<cite> van Noord and Bos (2017)</cite> . In a nutshell, this method uses a character-based sequence-to-sequence model to translate sentences to AMRs. To enable this process, pre-processing and post-processing steps are needed.