Journal Article


Andy Way
Sandipan Dandapat



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

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