Change search
ReferencesLink to record
Permanent link

Direct link
Nudging the Envelope of Direct Transfer Methods for Multilingual Named Entity Recognition
Number of Authors: 1
2012 (English)Conference paper (Refereed)
Abstract [en]

In this paper, we study direct transfer methods for multilingual named entity recognition. Specifically, we extend the method recently proposed by Täckström et al. (2012), which is based on cross-lingual word cluster features. First, we show that by using multiple source languages, combined with self-training for target language adaptation, we can achieve significant improvements compared to using only single source direct transfer. Second, we investigate how the direct transfer system fares against a supervised target language system and conclude that between 8,000 and 16,000 word tokens need to be annotated in each target language to match the best direct transfer system. Finally, we show that we can significantly improve target language performance, even after annotating up to 64,000 tokens in the target language, by simply concatenating source and target language annotations.

Place, publisher, year, edition, pages
2012, 9.
National Category
Computer and Information Science
URN: urn:nbn:se:ri:diva-15216OAI: diva2:1036532
NAACL-HLT 2012 Workshop on Inducing Linguistic Structure
Available from: 2016-10-13 Created: 2016-10-13

Open Access in DiVA

fulltext(271 kB)4 downloads
File information
File name FULLTEXT01.pdfFile size 271 kBChecksum SHA-512
Type fulltextMimetype application/pdf

By organisation
Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 4 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

ReferencesLink to record
Permanent link

Direct link