Cross-Lingual Link Discovery (CLLD) aims to automatically find links between documents written in different languages. In this paper, we first present a relatively simple yet effective methods for CLLD in Wiki collections, explaining the fndings that motivated their design. Our methods (team KMI) achieved in the NTCIR-10 CrossLink-2 evaluation the best overall results in the English to Chinese, Japanese and Korean (E2CJK) task and were the top performers in the Chinese, Japanese, Korean to English task (CJK2E)1 [Tang et al.,2013]. Though tested on these language combinations, the methods are language agnostic and can be easily applied to any other language combination with sufficient corpora and available pre-processing tools. In the second part of the paper, we provide an in depth analysis of the nature of the task, the evaluation metrics and the impact of the system components on the overall CLLD performance. We believe a good understanding of these aspects is the key to improving CLLD systems in the future
