Conference Proceeding Article
In this paper we present a novel approach to entity linking based on a statistical language model-based information retrieval with query expansion. We use both local contexts and global world knowledge to expand query language models. We place a strong emphasis on named entities in the local contexts and explore a positional language model to weigh them differently based on their distances to the query. Our experiments on the TAC-KBP 2010 data show that incorporating such contextual information indeed aids in disambiguating the named entities and consistently improves the entity linking performance. Compared with the official results from KBP 2010 participants, our system shows competitive performance.
Databases and Information Systems
Data Management and Analytics
EMNLP '11: Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, Edinburgh, Scotland, UK, July 27-31
Association for Computational Linguistics
City or Country
GOTTIPATI, Swapna and JIANG, Jing.
Linking Entities to a Knowledge Base with Query Expansion. (2011). EMNLP '11: Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, Edinburgh, Scotland, UK, July 27-31. 804-813. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1377
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.