Definition: In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.
Input: 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. Appendix, software, and data are available online at: http://slanglab.cs.umass. edu/PoliceKillingsExtraction/ [This paper appears in Proceedings of EMNLP 2017. This version includes the appendix.]

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