  Text generation systems are ubiquitous in natural language processing
applications. However, evaluation of these systems remains a challenge,
especially in multilingual settings. In this paper, we propose L'AMBRE -- a
metric to evaluate the morphosyntactic well-formedness of text using its
dependency parse and morphosyntactic rules of the language. We present a way to
automatically extract various rules governing morphosyntax directly from
dependency treebanks. To tackle the noisy outputs from text generation systems,
we propose a simple methodology to train robust parsers. We show the
effectiveness of our metric on the task of machine translation through a
diachronic study of systems translating into morphologically-rich languages.
