(2011) extracted ngram counts from Google queries and a large corpus to improve the MSTParser.
to previous work, we refer to our approach as self-learning because it differs from self-training by utilising statistics found using an initial parse ranking model to create a separate unsupervised reranking component, without retraining the baseline unlexicalised model.