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Relation extraction has been widely used for finding unknown relational facts from the plain text. Most existing methods focus on exploiting mono-lingual data for relation extraction, ignoring massive information from the texts in various languages. To address this issue, we introduce a multi-lingual neural relation extraction framework, which employs monolingual attention to utilize the information within mono-lingual texts and further proposes cross-lingual attention to consider thedoi:10.18653/v1/p17-1004 dblp:conf/acl/LinLS17 fatcat:qnpzfmi3g5hbvd7cn7p3veprny