  Meaning Representation (AMR) is a semantic representation for natural
language that embeds annotations related to traditional tasks such as named
entity recognition, semantic role labeling, word sense disambiguation and
co-reference resolution. We describe a transition-based parser for AMR that
parses sentences left-to-right, in linear time. We further propose a test-suite
that assesses specific subtasks that are helpful in comparing AMR parsers, and
show that our parser is competitive with the state of the art on the LDC2015E86
dataset and that it outperforms state-of-the-art parsers for recovering named
entities and handling polarity.
