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: 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?

A: there are several related passages for each question in the MS-MARCO dataset. MS-MARCO also annotates which passage is correct
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Q: We crowdsourced multiple-choice questions in two parts, encouraging workers to be imaginative and varied in their use of language. First, workers were given a seed qualitative relation q+/-( INLINEFORM0 ) in the domain, expressed in English (e.g., “If a surface has more friction, then an object will travel slower”), and asked to enter two objects, people, or situations to compare. 
 Question: Do all questions in the dataset allow the answers to pick from 2 options?

A: Yes
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Q: We tried Glove BIBREF2 and Twitter word2vec BIBREF3 code for training embeddings for the processed tweets. 
 Question: What embeddings do they use?

A:
Glove Twitter word2vec
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