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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 lan-guage, using a modified version of MSTPars-er. We did all the experiments on the ICON 2009 parsing contest data. We achieved an improvement of 0.87% and 0.77% in unla-beled attachment and labeled attachment accu-racies respectively over the baseline parsing accuracies.
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Added on March 5, 2012

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  • Product Type : Research Paper
  • License Type : Freeware
  • System Requirement : Not Applicable
  • Author : Phani Gadde,Karan Jindal,Samar Husain,Dipti Misra Sharma,Rajeev Sangal
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