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Each sentence token is associated with\na BiLSTM vector representing the token in its sentential context, and feature\nvectors are constructed by concatenating a few BiLSTM vectors. The BiLSTM is\ntrained jointly with the parser objective, resulting in very effective feature\nextractors for parsing. We demonstrate the effectiveness of the approach by\napplying it to a greedy transition-based parser as well as to a globally\noptimized graph-based parser. 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