Abstract
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.
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Chen, Z., Tamang, S., Lee, A., Li, X., Passantino, M., Ji, H. (2010). Top-Down and Bottom-Up: A Combined Approach to Slot Filling. In: Cheng, PJ., Kan, MY., Lam, W., Nakov, P. (eds) Information Retrieval Technology. AIRS 2010. Lecture Notes in Computer Science, vol 6458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17187-1_29
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DOI: https://doi.org/10.1007/978-3-642-17187-1_29
Publisher Name: Springer, Berlin, Heidelberg
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