کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4960342 1364894 2017 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Telugu dependency parsing using different statistical parsers
ترجمه فارسی عنوان
تجزیه وابستگی تلوگو با استفاده از تجزیه کننده های آماری مختلف
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی

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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of King Saud University - Computer and Information Sciences - Volume 29, Issue 1, January 2017, Pages 134-140
نویسندگان
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