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
- Venue:
- TACL
- SIG:
- Publisher:
- MIT Press
- Note:
- Pages:
- 259–272
- Language:
- URL:
- https://aclanthology.org/Q14-1021
- DOI:
- 10.1162/tacl_a_00181
- 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)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/Q14-1021.pdf