Type

Journal Article

Authors

Andy Way
Sandipan Dandapat

Subjects

Linguistics

Topics
phase machine translating named entity translation language machine translation support vector machine named entity recognition word alignment

Improved named entity recognition using machine translation-based cross-lingual information (2016)

Abstract In this paper, we describe a technique to improve named entity recognition in a resource-poor language (Hindi) by using cross-lingual information. We use an on-line machine translation system and a separate word alignment phase to find the projection of each Hindi word into the translated English sentence. We estimate the cross-lingual features using an English named entity recognizer and the alignment information. We use these cross-lingual features in a support vector machine-based classifier. The use of cross-lingual features improves F1 score by 2.1 points absolute (2.9% relative) over a good-performing baseline model.
Collections Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Computing
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: ADAPT
Ireland -> Dublin City University -> Publication Type = Article
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Machine translating

Full list of authors on original publication

Andy Way, Sandipan Dandapat

Experts in our system

1
Andy Way
Dublin City University
Total Publications: 229
 
2
Sandipan Dandapat
Dublin City University
Total Publications: 9