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.

The dataset includes about 6,000 triples, comprised of videos, questions, and answer spans manually collected from screencast tutorial videos with spoken narratives for a photo-editing software. 
What kind of instructional videos are in the dataset?

We used the relation classification dataset of the SemEval 2010 task 8 BIBREF8 . It consists of sentences which have been manually labeled with 19 relations (9 directed relations and one artificial class Other). 8,000 sentences have been distributed as training set and 2,717 sentences served as test set.
Which dataset do they train their models on?

n this paper we provide a novel real-time and adaptive cryptocurrency price prediction platform based on Twitter sentiments. The integrative and modular platform copes with the three aforementioned challenges in several ways. Firstly, it provides a Spark-based architecture which handles the large volume of incoming data in a persistent and fault tolerant way. Secondly, the proposed platform offers an approach that supports sentiment analysis based on VADER which can respond to large amounts of natural language processing queries in real time. Thirdly, the platform supports a predictive approach based on online learning in which a machine learning model adapts its weights to cope with new prices and sentiments. Finally, the platform is modular and integrative in the sense that it combines these different solutions to provide novel real-time tool support for bitcoin price prediction that is more scalable, data-rich, and proactive, and can help accelerate decision-making, uncover new opportunities and provide more timely insights based on the available and ever-larger financial data volume and variety.

Which elements of the platform are modular?

