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.

Example Input: We evaluated our models on 3 different datasets:

CSAT dataset for CSAT prediction, consisting of spoken transcripts (automatic via ASR).

20 newsgroups for topic identification task, consisting of written text;

Fisher Phase 1 corpus for topic identification task, consisting of spoken transcripts (manual);
Question: What datasets did they use for evaluation?
Example Output: CSAT dataset 20 newsgroups Fisher Phase 1 corpus

Example Input: 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?
Example Output: MemN2N BIBREF12 Attentive and Impatient Readers BIBREF6

Example Input: In the first task, participants were instructed to read the sentences naturally, without any specific task other than comprehension. Participants were told to read the sentences normally without any special instructions.
Question: What is a normal reading paradigm?
Example Output:
read the sentences normally without any special instructions