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Neural Relation Extraction with Multi-lingual Attention
2017
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
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 the
doi:10.18653/v1/p17-1004
dblp:conf/acl/LinLS17
fatcat:qnpzfmi3g5hbvd7cn7p3veprny