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.

[Q]: We tested the system on two datasets, different in size and complexity of the addressed language.

Experimental Evaluation ::: Datasets ::: NLU-Benchmark dataset
The first (publicly available) dataset, NLU-Benchmark (NLU-BM), contains $25,716$ utterances annotated with targeted Scenario, Action, and involved Entities. Experimental Evaluation ::: Datasets ::: ROMULUS dataset
The second dataset, ROMULUS, is composed of $1,431$ sentences, for each of which dialogue acts, semantic frames, and corresponding frame elements are provided. This dataset is being developed for modelling user utterances to open-domain conversational systems for robotic platforms that are expected to handle different interaction situations/patterns – e.g., chit-chat, command interpretation.
[A]: Which publicly available NLU dataset is used?


[Q]: CIC is a suitable complementary metric to ROUGE because it accounts for the most important information within each dialog domain. CIC can be applied to any summarization task with predefined essential entities.
[A]: Is new evaluation metric extension of ROGUE?


[Q]: Three annotators, A1-A3, mark each tweet in the Dataset H as drunk or sober.
[A]:
Is the data acquired under distant supervision verified by humans at any stage?