Translation by machine of complex nominals
Timothy J. Baldwin, Takaaki Tanaka · 2004
We present a method for compositionally translating noun-noun (NN) compounds, using a word-level bilingual dictionary and syntactic templates for candidate generation, and corpus and dictionary statistics for selection. We propose a support vector learning-based method employing target language corpus and bilingual dictionary data, and evaluate it over a English ↔ Japanese machine translation task. We show the proposed method to be superior to previous methods and also robust over low-frequency NN compounds.