A Hybrid Transliteration Model for Chinese/English Named Entities -BJTU-NLP Report for the 5th Named Entities Workshop

Abstract

This paper presents our system (BJTU-NLP system) for the NEWS2015 evaluation task of Chinese-to-English and Englis h-to-Chinese named entity transliteration. Our system adopts a hybrid machine transliteration approach, which combines several features. To further improve the result, we adopt external data extracted from wikipeda to expand the training set. In addition, pre-processing and post-processing rules are utilized to further improve the performance. The fina l performance on the test corpus shows that our system achieves comparable results with other state-of-the-art systems. c 2015 Association for Computational Linguistics.