Combining Supervised and Unsupervised Enembles for Knowledge Base Population
Nazneen Fatema Rajani, Raymond J. Mooney · 2016
We propose an algorithm that combines supervised and unsupervised methods to ensemble multiple systems for two popular Knowledge Base Population (KBP) tasks, Cold Start Slot Filling (CSSF) and Tri-lingual Entity Discovery and Linking (TEDL).We demonstrate that it outperforms the best system for both tasks in the 2015 competition, several ensembling baselines, as well as a state-of-the-art stacking approach.The success of our technique on two different and challenging problems demonstrates the power and generality of our combined approach to ensembling.