  Abstract Meaning Representation (AMR) is a recently designed semantic
representation language intended to capture the meaning of a sentence, which
may be represented as a single-rooted directed acyclic graph with labeled nodes
and edges. The automatic evaluation of this structure plays an important role
in the development of better systems, as well as for semantic annotation.
Despite there is one available metric, smatch, it has some drawbacks. For
instance, smatch creates a self-relation on the root of the graph, has weights
for different error types, and does not take into account the dependence of the
elements in the AMR structure. With these drawbacks, smatch masks several
problems of the AMR parsers and distorts the evaluation of the AMRs. In view of
this, in this paper, we introduce an extended metric to evaluate AMR parsers,
which deals with the drawbacks of the smatch metric. Finally, we compare both
metrics, using four well-known AMR parsers, and we argue that our metric is
more refined, robust, fairer, and faster than smatch.
