Query Lattice for Translation Retrieval

Abstract

Translation retrieval aims to find the most likely translation among a set of target-language strings for a given source-language string. Previous studies consider the single-best translation as a query for information retrieval, which may result in translation error propagation. To alleviate this problem, we propose to use the query lattice, which is a compact representation of exponentially many queries containing translation alternatives. We verified the effectiveness of query lattice through experiments, where our method explores a much larger search space (from 1 query to 1.24◊ 10 62 queries), runs much faster (from 0.75 to 0.13 second per sentence), and retrieves more accurately (from 83.76% to 93.16% in precision) than the standard method based on the query single-best. In addition, we show that query lattice significantly outperforms the method of (Munteanu and Marcu, 2005) on the task of parallel sentence mining from comparable corpora.