The effects of high quality translations of named entities in cross-language information exploration

Abstract

Named entities (NEs) are the expressions in human languages that explicitly link notations in languages to the entities in the real world. They play important role in cross-language information retrieval (CLIR) because most users' requests have been found to have NEs, and majority of out-of-vocabulary terms are NEs. Therefore, missing their translations has a significant impact to the retrieval effectiveness. In this paper, we examined the effect of high quality translations of NEs in event driven information exploration, where the existence of NEs is even more common. With the focus on the effect of NE translations obtained by using information extraction (IE) techniques, we conducted several experiments using TDT test collections. Our results demonstrate that NEs and their translations play critical roles in improving CLIR effectiveness, and it makes positive impact in CLIR to use high quality translations of NEs obtained by IE techniques.