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:
As shown in Table TABREF12, the T-T model significantly outperforms the LSTM-based RNN-T baseline.

Ex Output:
What was previous state of the art model?


Ex Input:
TOEFL listening comprehension test is for human English learners whose native language is not English. This paper reports how today's machine can perform with such a test.

The listening comprehension task considered here is highly related to Spoken Question Answering (SQA) BIBREF0 , BIBREF1 . 

Ex Output:
What is the new task proposed in this work?


Ex Input:
Due to the high cost of pre-training BERT language model, we directly adopt parameters pre-trained by Google in Chinese general corpus. The named entity recognition is applied on both pathology report texts and query texts.

Ex Output:

What data is the language model pretrained on?