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 Q]: Previous attempts to annotate QA-SRL initially involved trained annotators BIBREF4 but later resorted to crowdsourcing BIBREF5 to achieve scalability.
[EX A]: How was the corpus obtained?

[EX Q]: In terms of this, rather than starting from Twitter API Search, we look into the archived snapshots of two major news websites (CNN, NBC), and then extract the tweet blocks that are embedded in the news articles.
[EX A]: How do they determine if tweets have been used by journalists?

[EX Q]: The Business Language Testing Service (BULATS) test of Cambridge Assessment English BIBREF27 is a multi-level computer-based English test. It consists of read speech and free-speaking components, with the candidate responding to prompts. The BULATS spoken test has five sections, all with materials appropriate to business scenarios. In this work, non-native speech from the BULATS test is used as both training and test data for the speaker verification systems. To investigate how the systems generalise, data for testing is also taken from the Cambridge Assessment English Linguaskill online test. Like BULATS, this is also a multi-level test and has a similar format composed of the same five sections as described before but assesses general English ability.
[EX A]:
What standard large speaker verification corpora is used for evaluation?