Neural Relation Extraction with Multi-lingual Attention
Yankai Lin, Zhiyuan Liu, Maosong Sun · 2017
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 information consistency and complementarity among cross-lingual texts.Experimental results on real-world datasets show that our model can take advantage of multi-lingual texts and consistently achieve significant improvements on relation extraction as compared with baselines.The source code of this paper can be obtained from https://github.com/thunlp/MNRE