Inducing translations from officially published materials in Canadian government websites

Bitexts collected from web-based materials that are officially published on government websites can be used for a variety of purposes in language analysis and natural language processing. Mining officially published web pages can thus be an invaluable undertaking for translators in government departments who are producing the translations, and for machine translation researchers who are studying how those translations are produced. In this paper, we present the StatCan Daily Translation Extraction System (SDTES) and demonstrate how it is used to induce translations from officially published bilingual materials from government websites in Canada. New evaluation results show that SDTES is a very effective system for identifying and extracting sentences that are translation pairs from most of the federal government web pages which are currently under the CLF2 (Common Look and Feel for the Internet 2.0) framework.