Path: Top -> Journal -> Jurnal Internasional -> King Saud University -> 2017 -> Volume 29, Issue 1, January

Telugu dependency parsing using different statistical parsers

Journal from gdlhub / 2017-08-14 13:34:20
Oleh : B. Venkata Seshu Kumari , Ramisetty Rajeshwara Rao , King Saud University
Dibuat : 2017-01-14, dengan 1 file

Keyword : Dependency parsing Telugu MSTParser MaltParser TurboParser ZPar
Url : http://www.sciencedirect.com/science/article/pii/S1319157815000798
Sumber pengambilan dokumen : web

In this paper we explore different statistical dependency parsers for parsing Telugu. We consider five popular dependency parsers namely, MaltParser, MSTParser, TurboParser, ZPar and Easy-First Parser. We experiment with different parser and feature settings and show the impact of different settings. We also provide a detailed analysis of the performance of all the parsers on major dependency labels. 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 unlabeled attachment score and 70.0% in labeled attachment score. To the best of our knowledge ours is the only work which explored all the five popular dependency parsers and compared the performance under different feature settings for Telugu.

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PropertiNilai Properti
ID Publishergdlhub
OrganisasiKing Saud University
Nama KontakHerti Yani, S.Kom
AlamatJln. Jenderal Sudirman
KotaJambi
DaerahJambi
NegaraIndonesia
Telepon0741-35095
Fax0741-35093
E-mail Administratorelibrarystikom@gmail.com
E-mail CKOelibrarystikom@gmail.com

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