Identifying civilians killed by police with distantly supervised entity-event extraction

author: Brendan O'Connor, Machine Learning Department, School of Computer Science, Carnegie Mellon University
published: Dec. 1, 2017,   recorded: August 2017,   views: 3
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Description

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.

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