instruction:
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.
question:
Our goal was to generate questions without templates and with minimal human involvement using machine learning transformers that have been demonstrated to train faster and better than RNNs. Such a system would benefit educators by saving time to generate quizzes and tests.
answer:
What is the motivation behind the work? Why question generation is an important task?

question:
We define the STransE score function $\mathcal {R}$1 as follows:

$ f_r(h, t) & = & \Vert extbf {W}_{r,1} extbf {h} + extbf {r} - extbf {W}_{r,2} extbf {t}\Vert _{\ell _{1/2}} $

using either the $\ell _1$ or the $\ell _2$ -norm (the choice is made using validation data; in our experiments we found that the $\ell _1$ norm gave slightly better results).
answer:
What scoring function does the model use to score triples?

question:
Following the previous works, we perform 10-fold cross validation and report the average results.
answer:
How is the robustness of the model evaluated?