Publication Type
Journal Article
Version
publishedVersion
Publication Date
10-2014
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 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.
Discipline
Databases and Information Systems | Social Media
Research Areas
Data Science and Engineering
Publication
Transactions of the Association for Computational Linguistics
Volume
2
First Page
259
Last Page
272
ISSN
2307-387X
Identifier
10.1162/tacl_a_00181
Publisher
Association for Computational Linguistics
Citation
FANG, Yuan and CHANG, Ming-Wei.
Entity linking on microblogs with spatial and temporal signals. (2014). Transactions of the Association for Computational Linguistics. 2, 259-272.
Available at: https://ink.library.smu.edu.sg/sis_research/4073
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1162/tacl_a_00181
Comments
Invited for oral presentation at Conference on Empirical Methods on Natural Language Processing EMNLP 2014, October 25-29, Doha, Qatar