Identifying civilians killed by police with distantly supervised entity-event extraction
Katherine A. Keith, Abram Handler, Michael Pinkham, Cara Magliozzi, Joshua McDuffie, Brendan O’Connor · 2017
We propose a new, socially-impactful task for natural language processing: from a news corpus, extract names of persons who have been killed by police.We present a newly collected police fatality corpus, which we release publicly, and present a model to solve this problem that uses EM-based distant supervision with logistic regression and convolutional neural network classifiers.Our model outperforms two off-the-shelf event extractor systems, and it can suggest candidate victim names in some cases faster than one of the major manually-collected police fatality databases.