(2016) exploit both languagedependent and language-independent features in the form of universal features such as universal dependencies, limited bilingual dictionaries and aligned multilingual word embeddings to train a model with multiple languages.
this work lags behind in terms of the neural approach used and doesn't investigate the effectiveness of leveraging multiple source languages.