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 used two strategies in combining prediction results of two types of models. Specifically, the Max Score Ensemble model made the final decisions based on the maximum of two scores assigned by the two separate models; instead, the Average Score Ensemble model used the average score to make final decisions. 
 Question: How do they combine the models?
Example Output: maximum of two scores assigned by the two separate models average score

Example Input: The choice of two methods for our empirical study is motivated by the best performance achieved by Logistic Regression in question-question similarity at SemEval 2017 (best system BIBREF37 and second best system BIBREF38 ), and the high performance achieved by neural networks on larger datasets such as SNLI BIBREF13 , BIBREF39 , BIBREF40 , BIBREF41  
 Question: What machine learning and deep learning methods are used for RQE?
Example Output: Logistic Regression neural networks

Example Input: The CRF module achieved the best result on the Thai sentence segmentation task BIBREF8 ; therefore, we adopt the Bi-LSTM-CRF model as our baseline.  
 Question: Which deep learning architecture do they use for sentence segmentation?
Example Output:
Bi-LSTM-CRF