scholarly journals Shallow Parsing and Word Sense Disambiguation Used for Machine Translation from Hindi to English Languages

2017 ◽  
Vol 10 (3) ◽  
pp. 381-390
Author(s):  
Shachi Mall ◽  
◽  
Umesh Jaiswal ◽  
Author(s):  
David Vickrey ◽  
Luke Biewald ◽  
Marc Teyssier ◽  
Daphne Koller

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 38512-38523 ◽  
Author(s):  
Quang-Phuoc Nguyen ◽  
Anh-Dung Vo ◽  
Joon-Choul Shin ◽  
Cheol-Young Ock

2019 ◽  
Vol 20 (1) ◽  
pp. 107-140
Author(s):  
Nicolás José Fernández-Martínez ◽  
Pamela Faber

Abstract Drawing on the Lexical Grammar Model, Frame Semantics and Corpus Pattern Analysis, we analyze and contrast verbs of stealing in English and Spanish from a lexico-semantic perspective. This involves looking at the lexical collocates and their corresponding semantic categories that fill the argument slots of verbs of stealing. Our corpus search is performed with the Word Sketch tool on Sketch Engine. To the best of our knowledge, no study has yet taken advantage of the Word Sketch tool in the study of the selection preferences of verbs of stealing, let alone a semantic, cross-linguistic study of those verbs. Our findings reveal that English and Spanish verbs of stealing map out the same underlying semantic space. This shared conceptual layer can thus be incorporated into an ontology based on deep semantics, which could in turn enhance NLP tasks such as word sense disambiguation, machine translation, semantic tagging, and semantic parsing.


2014 ◽  
Vol 981 ◽  
pp. 153-156
Author(s):  
Chun Xiang Zhang ◽  
Long Deng ◽  
Xue Yao Gao ◽  
Li Li Guo

Word sense disambiguation is key to many application problems in natural language processing. In this paper, a specific classifier of word sense disambiguation is introduced into machine translation system in order to improve the quality of the output translation. Firstly, translation of ambiguous word is deleted from machine translation of Chinese sentence. Secondly, ambiguous word is disambiguated and the classification labels are translations of ambiguous word. Thirdly, these two translations are combined. 50 Chinese sentences including ambiguous words are collected for test experiments. Experimental results show that the translation quality is improved after the proposed method is applied.


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