Bootstrapping bilingual lexicons from comparable corpora for closely related languages

Abstract

In this paper we present an approach to bootstrap a Croatian-Slovene bilingual lexicon from comparable news corpora from scratch, without relying on any external bilingual knowledge resource. Instead of using a dictionary to translate context vectors, we build a seed lexicon from identical words in both languages and extend it with context-based cognates and translation candidates of the most frequent words. By enlarging the seed dictionary for only 7% we were able to improve the baseline precision from 0.597 to 0.731 on the mean reciprocal rank for the ten top-ranking translation candidates with a 50.4% recall on the gold standard of 500 entries. © 2011 Springer-Verlag.