Top-Down and Bottom-Up: A Combined Approach to Slot Filling

The Slot Filling task requires a system to automatically distill information from a large document collection and return answers for a query entity with specified attributes (`slots'), and use them to expand the Wikipedia infoboxes. We describe two bottom-up Information Extraction style pipelines and a top-down Question Answering style pipeline to address this task. We propose several novel approaches to enhance these pipelines, including statistical answer re-ranking and Markov Logic Networks based cross-slot reasoning. We demonstrate that our system achieves state-of-the-art performance, with 3.1% higher precision and 2.6% higher recall compared with the best system in the KBP2009 evaluation.

• Type: Journal
• Year: 2010
• Where: AIRS
• Authors: Zheng Chen, Suzanne Tamang, Adam Lee, Xiang Li, Marissa Passantino, Heng Ji
• Keywords: AIRS 2010, Extraction Style Pipelines, Information Technology, Question Answering Style, Style Pipeline