Named entity translation is indispensable in cross language information retrieval nowadays. We propose an approach of combining lexical information, web statistics, and inverse search based on Google to backward translate a Chinese named entity (NE) into English. Our system achieves a high Top-1 accuracy of 87.6%, which is a relatively good performance reported in this area until present.
REF used the combination of Web statistics and the vocabulary, and acquired the Top-1 accuracy of 87.6% in Chinese-English OOV word translation.
A High-Accurate Chinese-English NE Backward Translation System Combining Both Lexical Information And Web Statistics
International Conference On Computational Linguistics And Annual Meeting Of The Association For Computational Linguistics - Poster Sessions
Computer Science