Entity Linking on Microblogs with Spatial and Temporal Signals

Yuan Fang, Ming-Wei Chang


Abstract
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 annotations 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.
Anthology ID:
Q14-1021
Volume:
Transactions of the Association for Computational Linguistics, Volume 2
Month:
Year:
2014
Address:
Cambridge, MA
Editors:
Dekang Lin, Michael Collins, Lillian Lee
Venue:
TACL
SIG:
Publisher:
MIT Press
Note:
Pages:
259–272
Language:
URL:
https://aclanthology.org/Q14-1021
DOI:
10.1162/tacl_a_00181
Bibkey:
Cite (ACL):
Yuan Fang and Ming-Wei Chang. 2014. Entity Linking on Microblogs with Spatial and Temporal Signals. Transactions of the Association for Computational Linguistics, 2:259–272.
Cite (Informal):
Entity Linking on Microblogs with Spatial and Temporal Signals (Fang & Chang, TACL 2014)
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PDF:
https://aclanthology.org/Q14-1021.pdf