  AMR parsing is the task that maps a sentence to an AMR semantic graph
automatically. We focus on the breadth-first strategy of this task, which was
proposed recently and achieved better performance than other strategies.
However, current models under this strategy only \emph{encourage} the model to
produce the AMR graph in breadth-first order, but \emph{cannot guarantee} this.
To solve this problem, we propose a new architecture that \emph{guarantees}
that the parsing will strictly follow the breadth-first order. In each parsing
step, we introduce a \textbf{focused parent} vertex and use this vertex to
guide the generation. With the help of this new architecture and some other
improvements in the sentence and graph encoder, our model obtains better
performance on both the AMR 1.0 and 2.0 dataset.
