A heuristic framework for pivot-based bilingual dictionary induction

High quality machine readable dictionaries are very useful, but such resources are rarely available for lower-density language pairs, especially for those that are closely related. In this paper, we proposed a heuristic framework that aims at inducing one-to-one mapping dictionary of a closely related language pair from available dictionaries where a distant language is involved. The key insight of the framework is the ability to create heuristics by using distant language as pivot, incorporate given heuristics, and an iterative induction mechanism that human interaction can be potentially integrated. An experiment based on basic heuristics regarding syntactics and semantics resulted in up to 85.2% correctness in target dictionary with correctness of major part reached 95.3%, which proved that we can perform automated creation of a high quality dictionary with our framework.