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: The CoNLL-2012 shared task BIBREF21 corpus is used as the evaluation dataset, which is selected from the Ontonotes 5.0. 
 Question: What dataset do they evaluate their model on?
Example Output: CoNLL-2012 shared task BIBREF21 corpus

Example Input: This model consists of two identical RNN encoders with no shared parameters, as well as a standard RNN decoder. For each target sentence, two versions of the source sentence are used: the sequential (standard) version and the linearized parse (lexicalized or unlexicalized). 
 Question: What kind of encoders are used for the parsed source sentence?
Example Output:
RNN encoders