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Exploring Different Approaches for Parsing Telugu

  • B. Venkata Seshu KumariEmail author
  • A. Giri Prasaad
  • M. Susmitha
  • Vikram Raju R.
  • Roheet Bhatnagar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 921)

Abstract

In this paper we explore different approaches for parsing Telugu. We consider three popular dependency parsers namely, MaltParser, MSTParser and TurboParser. We first experiment with different parser and feature settings and show the impact of different settings. We then explore different ways of ensembling these parsers. We also provide a detailed analysis of the performance of all the approaches on major dependency labels and different distance ranges. We report our results on test data of Telugu dependency treebank provided in the ICON 2010 tools contest on Indian languages dependency parsing. We obtain state-of-the art performance of 91.8% in unlabelled attachment score and 70.0% in labelled attachment score.

Keywords

Dependency parsing Telugu MSTParser MaltParser TurboParser 

Notes

Acknowledgements

We would also like to thank Language Technologies Research Centre (LTRC), International Institute of Information Technology, Hyderabad (IIIT-H) for providing the Telugu dependency treebank.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • B. Venkata Seshu Kumari
    • 1
    Email author
  • A. Giri Prasaad
    • 1
  • M. Susmitha
    • 1
  • Vikram Raju R.
    • 1
  • Roheet Bhatnagar
    • 2
  1. 1.Department of ITVNR VJIETHyderabadIndia
  2. 2.Department of Computer Science and EngineeringManipal University JaipurJaipurIndia

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