Abstract
Gazetteers or entity dictionaries are important knowledge resources for solving a wide range of NLP problems, such as entity extraction. We introduce a novel method to automatically generate gazetteers from seed lists using an external knowledge resource, the Wikipedia. Unlike previous methods, our method exploits the rich content and various structural elements of Wikipedia, and does not rely on language- or domain-specific knowledge. Furthermore, applying the extended gazetteers to an entity extraction task in a scientific domain, we empirically observed a significant improvement in system accuracy when compared with those using seed gazetteers.
Cite
CITATION STYLE
Zhang, Z., & Iria, J. (2009). A novel approach to automatic gazetteer generation using Wikipedia. In People’s Web 2009 - 2009 Workshop on The People’s Web Meets NLP: Collaboratively Constructed Semantic Resources at the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, ACL-IJCNLP 2009 - Proceedings (pp. 1–9). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1699765.1699766
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