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Motivated by a continually increasing demand for applications that depend on machine comprehension of text-based content, researchers, in both academia and industry, have developed innovative solutions for automated information extraction from text. In this article, we focus on a subset of such toolsi.e., semantic taggersthat not only extract and disambiguate entities mentioned in the text, but also identify topics that unambiguously describe the text's main themes. We offer insight into thedoi:10.1109/mitp.2014.85 fatcat:lklbciaiyrh7dh6fhw55zcpdge