A Multi-media Approach to Cross-lingual Entity Knowledge Transfer

Di Lu, Xiaoman Pan, Nima Pourdamghani, Shih-Fu Chang, Heng Ji, Kevin Knight
2016 Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)  
When a large-scale incident or disaster occurs, there is often a great demand for rapidly developing a system to extract detailed and new information from lowresource languages (LLs). We propose a novel approach to discover comparable documents in high-resource languages (HLs), and project Entity Discovery and Linking results from HLs documents back to LLs. We leverage a wide variety of language-independent forms from multiple data modalities, including image processing (image-to-image
more » ... , visual similarity and face recognition) and sound matching. We also propose novel methods to learn entity priors from a large-scale HL corpus and knowledge base. Using Hausa and Chinese as the LLs and English as the HL, experiments show that our approach achieves 36.1% higher Hausa name tagging F-score over a costly supervised model, and 9.4% higher Chineseto-English Entity Linking accuracy over state-of-the-art.
doi:10.18653/v1/p16-1006 dblp:conf/acl/LuPPCJK16 fatcat:te3lsl65ifhgbbwi6b6q54aaka