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 Input:
In particular, we investigated attention to nouns, verbs, pronouns, subjects, objects, and negation words, and special BERT tokens across the tasks.

Ex Output:
What handcrafter features-of-interest are used?


Ex Input:
As shown in Table TABREF46, consensus dropout fusion improves the score of NDCG by around 1.0 from the score of the joint model while still yielding comparable scores for other metrics. As also shown in Table TABREF46, the ensemble model seems to take the best results from each model.

Ex Output:
Which method for integration peforms better ensemble or consensus dropout fusion with shared parameters?


Ex Input:
For training, three types of Recurrent Neural Network (RNN) layers are used – an encoder layer, a decoder layer and an output layer. These layers together form a LSTM model. LSTM is typically used in seq2seq translation.

Ex Output:

What is the architecture of the system?