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News archives are an invaluable primary source for placing current events inhistorical context. But current search engine tools do a poor job at uncoveringbroad themes and narratives across documents. We present Rookie: a practicalsoftware system which uses natural language processing (NLP) to help readers,reporters and editors uncover broad stories in news archives. Unlike priorwork, Rookie's design emerged from 18 months of iterative development inconsultation with editors and computational journalists. This process lead to adramatically different approach from previous academic systems with similargoals. Our efforts offer a generalizable case study for others buildingreal-world journalism software using NLP.

Rookie: A unique approach for exploring news archives