TASK DEFINITION: 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.
PROBLEM: 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?

SOLUTION: Friends EmotionPush

PROBLEM: We compare our model with two sets of baselines:

MemN2N BIBREF12 is an end-to-end trainable version of memory networks BIBREF9 . Attentive and Impatient Readers BIBREF6 use bidirectional LSTMs to encode question and evidence, and do classification over a large vocabulary based on these two encodings. 
 Question: What are the baselines?

SOLUTION: MemN2N BIBREF12 Attentive and Impatient Readers BIBREF6

PROBLEM: To deal with negative values, we propose clipped $\mathit {PMI}$,

which is equivalent to $\mathit {PPMI}$ when $z = 0$. In practice we find this works poorly if done symmetrically, so we introduce a variant called $\mathit {NNEGPMI}$ which only normalizes $\mathit {\texttt {-}PMI}$: 
 Question: What novel PMI variants are introduced?

SOLUTION:
clipped PMI; NNEGPMI