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.
CITATION STYLE
Jakubina, L., & Langlais, P. (2017). Reranking translation candidates produced by several bilingualword similarity sources. In 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference (Vol. 2, pp. 605–611). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/e17-2096
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