Browsing by Author "Rao, Delip"
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Item Entity Disambiguation for Knowledge Base Population(2010-08-23) Dredze, Mark; McNamee, Paul; Rao, Delip; Gerber, Adam; Finin, TimThe integration of facts derived from information extraction systems into existing knowledge bases requires a system to disambiguate entity mentions in the text. This is challenging due to issues such as non-uniform variations in entity names, mention ambiguity, and entities absent from a knowledge base. We present a state of the art system for entity disambiguation that not only addresses these challenges but also scales to knowledge bases with several million entries using very little resources. Further, our approach achieves performance of up to 95% on entities mentioned from newswire and 80% on a public test set that was designed to include challenging queries.Item HLTCOE Approaches to Knowledge Base Population at TAC 2009(National Institute of Standards and Technology, 2009-11-01) McNamee, Paul; Dredze, Mark; Gerber, Adam; Garera, Nikesh; Finin, Tim; Mayfield, James; Piatko, Christine; Rao, Delip; Yarowsky, David; Dreyer, MarkusThe HLTCOE participated in the entity linking and slot filling tasks at TAC 2009. A machine learning-based approach to entity linking, operating over a wide range of feature types, yielded good performance on the entity linking task. Slot-filling based on sentence selection, application of weak patterns and exploitation of redundancy was ineffective in the slot filling task.