Sciweavers

Share
ACL
2008

Combining Source and Target Language Information for Name Tagging of Machine Translation Output

9 years 12 months ago
Combining Source and Target Language Information for Name Tagging of Machine Translation Output
A Named Entity Recognizer (NER) generally has worse performance on machine translated text, because of the poor syntax of the MT output and other errors in the translation. As some tagging distinctions are clearer in the source, and some in the target, we tried to integrate the tag information from both source and target to improve target language tagging performance, especially recall. In our experiments with Chinese-to-English MT output, we first used a simple merge of the outputs from an ET (Entity Translation) system and an English NER system, getting an absolute gain of 7.15% in F-measure, from 73.53% to 80.68%. We then trained an MEMM module to integrate them more discriminatively, and got a further average gain of 2.74% in F-measure, from 80.68% to 83.42%.
Shasha Liao
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where ACL
Authors Shasha Liao
Comments (0)
books