instruction:
In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
question:
EmotionLines BIBREF6 is a dialogue dataset composed of two subsets, Friends and EmotionPush, according to the source of the dialogues.
Question: what datasets were used?
answer:
Friends EmotionPush

question:
We build on the state-of-the-art publicly available question answering system by docqa. The system extends BiDAF BIBREF4 with self-attention and performs well on document-level QA.
Question: What is the underlying question answering algorithm?
answer:
The system extends BiDAF BIBREF4 with self-attention

question:
Throughout this article, we use two different embedding spaces. The first is the widely used representation built on GoogleNews BIBREF8 . The second is taken from BIBREF2 , and was trained on a Reddit dataset BIBREF9 .
Question: Which embeddings do they detect biases in?
answer:
Word embeddings trained on GoogleNews and Word embeddings trained on Reddit dataset