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.

Ex 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). 

Ex Output:
What are the benchmark models?


Ex Input:
We conduct our experiments on $\sim $ 8.7M annotated anonymised user utterances. They are annotated and derived from requests across 23 domains.

Ex Output:
Over which datasets/corpora is this work evaluated?


Ex Input:
One example illustrates that the mistakes the model makes can be associated with changes in the party policy.

Ex Output:

Do changes in policies of the political actors account for all of the mistakes the model made?