On one hand, we utilize their shared semantics to align similar words and entities with similar embedding vectors, no matter they are in the same language or not.
our embeddings are helpful to break down language gaps in many tasks, such as cross-lingual entity linking, in which the major challenge lies in measuring the similarity between entities and corresponding mentioned words in different languages.