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 map each relation type $R(x,y)$ to at least one parametrized natural-language question $q_x$ whose answer is $y$ .
[A]: How is the input triple translated to a slot-filling task?


[Q]: The current release of Katecheo uses a Bi-Directional Attention Flow, or BiDAF, model for reading comprehension BIBREF6 . Future releases of Katecheo will include the ability to swap out the reading comprehension model for newer architectures based on, e.g., BERT BIBREF8 or XLNet BIBREF9 or custom trained models.

Architecture and Configuration
[A]: what pretrained models were used?


[Q]: In multitask learning, a set of related tasks are learned (e.g., emotional activation), along with a primary task (e.g., emotional valence); both tasks share parts of the network topology and are hence jointly trained, as depicted in Figure FIGREF4 .
[A]:
What are the tasks in the multitask learning setup?