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 domainspecific 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.
REF use a novel entity extraction method to automatically generate gazetteers from seed lists using Wikipedia as knowledge source.
A Novel Approach to Automatic Gazetteer Generation using Wikipedia
Proceedings of the 2009 Workshop on The People’s Web Meets NLP: Collaboratively Constructed Semantic Resources (People's Web)
Computer Science