Before revision:  In this paper, we claim that , under the low-resource language setting , outside-Wikipedia cross-lingual resources are essential. To prove this argument, we propose a simple but effective zero-shot framework, CogCompXEL, that complements current methods by utilizing query log mapping files from online search engines . CogCompXEL outperforms current state-of-the-art models on almost all 25 languages of the LORELEI dataset, achieving an absolute average increase of 25 \% in gold candidate recall.
After revision:  In this paper, we claim that , under the low-resource language setting , outside-Wikipedia cross-lingual resources and present a simple yet effective zero-shot framework, CogCompXEL, that complements current methods by utilizing query log mapping files from online search engines . CogCompXEL outperforms current state-of-the-art models on almost all 25 languages of the LORELEI dataset, achieving an absolute average increase of 25 \% in gold candidate recall.