Using English Baits to Catch Serbian Multi-Word Terminology

Abstract

In this paper we present the first results in bilingual terminology extraction. The hypothesis of our approach is that if for a source language domain terminology exists as well as a domain aligned corpus for a source and a target language, then it is possible to extract the terminology for a target language. Our approach relies on several resources and tools: aligned domain texts, domain terminology for a source language, a terminology extractor for a target language, and a tool for word and chunk alignment. In this first experiment a source language is English, a target language is Serbian, a domain is Library and Information Science for which a bilingual terminological dictionary exists. Our term extractor is based on e-dictionaries and shallow parsing, and for word alignment we use GIZA++. At the end of procedure we included a supervised binary classifier that decides whether an extracted term is a valid domain term. The classifier was evaluated in a 5-fold cross validation setting on a slightly unbalanced dataset, maintaining average F-score of 89%. After conducting the experiment our system extracted 846 different Serbian domain phrases, containing 515 Serbian phrases that were not present in the existing domain terminology.

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