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.

Ex Input:
It is interesting to observe that the baseline model amplifies the bias in the training data set as measured by INLINEFORM0 and INLINEFORM1 . From measurements using the described bias metrics, our method effectively mitigates bias in language modelling without a significant increase in perplexity. 
 Question: how is mitigation of gender bias evaluated?

Ex Output:
Using INLINEFORM0 and INLINEFORM1


Ex Input:
Results in Table TABREF13 show ten probes. Again, we see the performance of baseline ELMo-transformer and mSynC are similar, with mSynC doing slightly worse on 7 out of 9 tasks. 
 Question: For how many probe tasks the shallow-syntax-aware contextual embedding perform better than ELMo’s embedding?

Ex Output:
performance of baseline ELMo-transformer and mSynC are similar, with mSynC doing slightly worse on 7 out of 9 tasks


Ex Input:
The baselines are: (a) trained on S-SQuAD, (b) trained on T-SQuAD and then fine-tuned on S-SQuAD, and (c) previous best model trained on S-SQuAD BIBREF5 by using Dr.QA BIBREF20 . The proposed approach (row (f)) outperforms previous best model (row (c)) by 2% EM score and over 1.5% F1 score. 
 Question: What was the previous best model?

Ex Output:

(c) previous best model trained on S-SQuAD BIBREF5 by using Dr.QA BIBREF20 


