文章基本信息

标题：A HYBRID PARSER MODEL FOR HINDI LANGUAGE
本地全文：下载
作者：Sneha Asopa ; Neelam Sharma
期刊名称：Indian Journal of Computer Science and Engineering
印刷版ISSN：2231-3850
电子版ISSN：0976-5166
出版年度：2021
卷号：12
期号：1
页码：271-277
DOI：10.21817/indjcse/2021/v12i1/211201223
出版社：Engg Journals Publications
摘要：Analyzing syntactic structure is the most complicated task for Indian Languages. In this paper, a probabilistic parser is proposed for Hindi language comprising the empirical and rationalist approaches. The task of tagging is accomplished with the help of TnT POS tagger. In this research work, along with the development and evaluation of probabilistic parser, evaluation of rule based and conditional random fields (CRF) based shallow parser is also done by using a test dataset of 100 tagged sentences of Hindi. The generation of probabilistic parser is formulated mainly by using rule based shallow parser, constructing grammar rules and assigning probabilities. The proposed probabilistic parser has shown the accuracy of 66%.
关键词：Hindi; parser; conditional random fields; rule based; probabilistic context free grammar.