Entity linking on microblogs with spatial and temporal signals

• Main Authors: FANG, Yuan, CHANG, Ming-Wei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2014
• Subjects: Databases and Information Systems; Social Media
• Online Access: https://ink.library.smu.edu.sg/sis_research/4073; https://ink.library.smu.edu.sg/context/sis_research/article/5076/viewcontent/Entity_linking_on_microblogs_2014_pv_oa.pdf
• Institution: Singapore Management University

Microblogs present an excellent opportunity for monitoring and analyzing world happenings. Given that words are often ambiguous, entity linking becomes a crucial step towards understanding microblogs. In this paper, we re-examine the problem of entity linking on microblogs. We first observe that spatiotemporal (i.e., spatial and temporal) signals play a key role, but they are not utilized in existing approaches. Thus, we propose a novel entity linking framework that incorporates spatiotemporal signals through a weakly supervised process. Using entity annotations1 on real-world data, our experiments show that the spatiotemporal model improves F1 by more than 10 points over existing systems. Finally, we present a qualitative study to visualize the effectiveness of our approach.