Improving data driven dependency parsing using clausal information

Abstract The paper describes a data driven dependency parsing approach which uses information about the clauses in a sentence to improve the parser performance. The clausal information is added automatically using a partial parser. We demonstrate the experiments on Hindi, a morphologically rich, free-word-order language, using a modified version of MSTParser. We did all the experiments on the ICON 2009 parsing contest data. We achieved an improvement of 0.87% and 0.77% in unlabeled attachment and labeled attachment accuracies respectively over the baseline parsing accuracies