  This article briefly explains our submitted approach to the DocEng'19
competition on extractive summarization. We implemented a recurrent neural
network based model that learns to classify whether an article's sentence
belongs to the corresponding extractive summary or not. We bypass the lack of
large annotated news corpora for extractive summarization by generating
extractive summaries from abstractive ones, which are available from the CNN
corpus.
