Reranking Translation Candidates produced by several Bilingual Word Similarity Sources


We investigate the reranking of the output of several distributional approaches on the Bilingual Lexicon Induction task. We show that reranking an n-best list produced by any of those approaches leads to very substantial improvements. We further demonstrate that combining several n-best lists by reranking is an effective way of further boosting performance.

European Chapter of the Association for Computational Linguistics (EACL’17)