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.

Example Input: We crowdsourced multiple-choice questions in two parts, encouraging workers to be imaginative and varied in their use of language. First, workers were given a seed qualitative relation q+/-( INLINEFORM0 ) in the domain, expressed in English (e.g., "If a surface has more friction, then an object will travel slower"), and asked to enter two objects, people, or situations to compare.
Example Output: Do all questions in the dataset allow the answers to pick from 2 options?

Example Input: We use English translations of the Chinese source texts in the WMT 2017 EnglishChinese test set BIBREF18 for all experiments presented in this article:
Example Output: What languages do they investigate for machine translation?

Example Input: Hot spots were originally annotated with 8 levels and degrees, ranging from 'not hot' to 'luke warm' to 'hot +'. Every utterance was labeled with one of these discrete labels by a single annotator. Hightened involvement is rare, being marked on only 1% of utterances.
Example Output:
What annotations are available in ICSI meeting corpus?