In the graphbased parser, we jointly train a structured-prediction model on top of a BiLSTM, propagating errors from the structured objective all the way back to the BiLSTM feature-encoder.
when training in this way the parser sees only configurations that result from following correct actions, and as a result tends to suffer from error propagation at test time.