Projective dependency parsing with perceptron

We describe an online learning dependency parser for the CoNLL-X Shared Task, based on the bottom-up projective algorithm of Eisner (2000). We experiment with a large feature set that models: the tokens involved in dependencies and their immediate context, the surface-text distance between tokens, and the syntactic context dominated by each dependency. In experiments, the treatment of multilingual information was totally blind.