In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

We focus here on the Europarl domain, for which we have ample data in several languages, and use as in-domain training data the Europarl corpus BIBREF5 for two translation directions: English INLINEFORM0 German and English INLINEFORM1 French. When measuring out-of-domain performance, we will use the WMT newstest 2014. or French we use samples from News-Commentary-11 and Wikipedia from WMT 2014 shared translation task, as well as the Multi-UN BIBREF9 and EU-Bookshop BIBREF10 corpora. For German, we use samples from News-Commentary-11, Rapid, Common-Crawl (WMT 2017) and Multi-UN (see table TABREF5 ). 
what dataset is used?

Comparing these topics with those that appeared on a Catholic women forum, it seems that both ISIS and non-violent groups use topics about motherhood, spousal relationship, and marriage/divorce when they address women. Moreover, we used Depechemood methods to analyze the emotions that these materials are likely to elicit in readers. The result of our emotion analysis suggests that both corpuses used words that aim to inspire readers while avoiding fear. However, the actual words that lead to these effects are very different in the two contexts. Overall, our findings indicate that, using proper methods, automated analysis of large bodies of textual data can provide novel insight insight into extremist propaganda that can assist the counterterrorism community.
What conclusions do the authors draw from their finding that the emotional appeal of ISIS and Catholic materials are similar?

In this study, we concentrate our effort on re-assessing keyphrase extraction performance on three increasingly sophisticated levels of document preprocessing described below.

what keyphrase extraction models were reassessed?

