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.

Input: Consider Input: For de-identification tasks, the three metrics we will use to evaluate the performance of our architecture are Precision, Recall and INLINEFORM0 score as defined below. 
 Question: What evaluation metrics do they use?

Output: Precision, Recall and INLINEFORM0 score


Input: Consider Input: Unlike the SQuAD dataset, which only has one passage given a question, there are several related passages for each question in the MS-MARCO dataset. In addition to annotating the answer, MS-MARCO also annotates which passage is correct.  
 Question: Why MS-MARCO is different from SQuAD?

Output: there are several related passages for each question in the MS-MARCO dataset. MS-MARCO also annotates which passage is correct


Input: Consider Input: To compare our results, we use the provided baseline, which is a non-parameter optimized linear-kernel SVM that uses TF-IDF bag-of-word vectors as inputs.  
 Question: What was the baseline model?


Output: a non-parameter optimized linear-kernel SVM that uses TF-IDF bag-of-word vectors as inputs