News stories are typically rich in NEs and therefore, comparable news corpora can be expected to contain NETEs (Klementiev and Roth, 2006; Tao et al., 2006). The large quantity and the perpetual availability of news corpora in many of the world’s languages, make mining of NETEs a viable alternative to traditional approaches. It is this opportunity that we address in our work. In this paper, we detail an effective and scalable mining method, called MINT (MIning Named-entity Transliteration equivalents), for mining of NETEs from large comparable corpora. .
