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.

Input: Consider Input: The neural machine translation was trained using Nematus. For the NMT system as well as for the PreMT system, we used the default configuration.

Output: Which NMT architecture do they use?

Input: Consider Input: We adapted BERTNLU from ConvLab-2. We implemented a rule-based model (RuleDST) and adapted TRADE (Transferable Dialogue State Generator) BIBREF19 in this experiment. We adapted a vanilla policy trained in a supervised fashion from ConvLab-2 (SL policy).

Output: What are the benchmark models?

Input: Consider Input: As with INLINEFORM0 , Greens-EFA, S&D, and EPP exhibit the highest cohesion, even though their ranking is permuted when compared to the ranking obtained with INLINEFORM1 . At the other end of the scale, we observe the same situation as with INLINEFORM2 . The non-aligned members NI have the lowest cohesion, followed by EFDD and ENL. The only place where the two methods disagree is the level of cohesion of GUE-NGL. The Alpha attributes GUE-NGL a rather high level of cohesion, on a par with ALDE, whereas the ERGM attributes them a much lower cohesion.
Output: What insights does the analysis give about the cohesion of political groups in the European parliament?