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:
Last but not least, ethics and fairness are important considerations, that deserve to be studied. In that sense, detection of individual and global bias should be prioritized in order to give useful feedbacks to practitioners. Furthermore we are considering using adversarial learning as in BIBREF33 in order to ensure fairness during the training process.
answer:
Is there any ethical consideration in the research?


question:
We use 16 different datasets from several popular review corpora used in BIBREF20 . These datasets consist of 14 product review datasets and two movie review datasets. We use CoNLL 2000 BIBREF22 sequence labeling dataset for both POS Tagging and Chunking tasks.
answer:
What dataset did they use?


question:
Our training data consists of 2.09M sentence pairs extracted from LDC corpus.
answer:

Where does the vocabulary come from?