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Reporting Bias and Knowledge Extraction
Jonathan Gordon, Benjamin Van Durme
Jun 29, 2013 (modified: Jun 29, 2013)AKBC 2013 submissionreaders: everyone
Abstract:Much work in knowledge extraction from text tacitly assumes that the frequency with which people write about actions, outcomes, or properties is a reflection of real-world frequencies or the degree to which a property is characteristic of a class of individuals. In this paper, we question this idea, examining the phenomenon of reporting bias and the challenge it poses for knowledge extraction. We conclude with discussion of approaches to learning commonsense knowledge from text in spite of this distortion.
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