  Previous approaches to multilingual semantic dependency parsing treat
languages independently, without exploiting the similarities between semantic
structures across languages. We experiment with a new approach where we combine
resources from a pair of languages in the CoNLL 2009 shared task to build a
polyglot semantic role labeler. Notwithstanding the absence of parallel data,
and the dissimilarity in annotations between languages, our approach results in
an improvement in SRL performance on multiple languages over a monolingual
baseline. Analysis of the polyglot model shows it to be advantageous in
lower-resource settings.
