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.

Q: As shown in Table , the proposed PS-rnn-elmo shows a significant MAP performance improvement compared to the previous best model, CompClip-LM (0.696 to 0.734 absolute). 
 Question: How much better performance of proposed model compared to answer-selection models?

A: significant MAP performance improvement compared to the previous best model, CompClip-LM (0.696 to 0.734 absolute)
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Q: For a word belonging to any one of the word-groups representing these concepts, the modified cost term favors an increase for the value of this word's embedding vector dimension corresponding to the concept that the particular word belongs to.  
 Question: Along which dimension do the semantically related words take larger values?

A: dimension corresponding to the concept that the particular word belongs to
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Q: During the final training process, 500 validation data is used to generate the recurrent neural model, which is 3% of the training data. After finishing the training, the accuracy of the generated model using validation data from the source corpus was 74.40% 
 Question: What dataset is used to measure accuracy?

A:
validation data
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