Lightly-Supervised Attribute Extraction(2007)
AbstractWeb search engines can greatly benefit from knowledge about attributes of entities present in search queries. In this paper, we introduce lightly-supervised methods for extracting entity attributes from natural language text. Using these methods, we are able to extract large numbers of attributes of different entities at fairly high precision from a large natural language corpus. We compare our methods against a previously proposed pattern-based relation extractor, showing that the new methods give considerable improvements over that baseline. We also demonstrate that query expansion using extracted attributes improves retrieval performance on underspecified information-seeking queries.
Citation InformationKedar Bellare, Partha Pratim Talukdar, Giridhar Kumaran, Fernando Pereira, et al.. "Lightly-Supervised Attribute Extraction" (2007)
Available at: http://works.bepress.com/andrew_mccallum/97/