Bilingual Dictionary Induction as an Optimization Problem

Abstract

Bilingual dictionaries are vital in many areas of natural language processing, but such resources are rarely available for lower-density language pairs, especially for those that are closely related. Pivot-based induction consists of using a third language to bridge a language pair. As an approach to create new dictionaries, it can generate wrong translations due to polysemy and ambiguous words. In this paper we propose a constraint approach to pivot-based dictionary induction for the case of two closely related languages. In order to take into account the word senses, we use an approach based on semantic distances, in which possibly missing translations are considered, and instance of induction is encoded as an optimization problem to generate new dictionary. Evaluations show that the proposal achieves 83.7% accuracy and approximately 70.5% recall, thus outperforming the baseline pivot-based method.

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