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.
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Question: Embedding: We developed different variations of our models with a simple lookup table embeddings learned from scratch and using high-performance contextual embeddings, which are ELMo BIBREF11, BERT BIBREF16 and ClinicalBERT BIBREF13 (trained and provided by the authors). 
 Question: What embeddings are used?

Answer:  simple lookup table embeddings learned from scratch using high-performance contextual embeddings, which are ELMo BIBREF11, BERT BIBREF16 and ClinicalBERT BIBREF13


Question: We also did a qualitative study on the Starbucks (SBUX) stock movement during this event. Figure FIGREF12 is the daily percentage change of SBUX and NASDAQ index between April 11th and April 20th. SBUX did not follow the upward trend of the whole market before April 17th, and then its change on April 20th, INLINEFORM0 , is quite significant from historical norms. We collected the historical 52 week stock prices prior to this event and calculated the daily stock price change. The distribution of the daily price change of the previous 52 weeks is Figure FIGREF13 with a mean INLINEFORM1 and standard deviation INLINEFORM2 .  
 Question: How does the method measure the impact of the event on market prices?

Answer: We collected the historical 52 week stock prices prior to this event and calculated the daily stock price change. The distribution of the daily price change of the previous 52 weeks is Figure FIGREF13 with a mean INLINEFORM1 and standard deviation INLINEFORM2 . 


Question: We obtained a corpus of approximately 300,000 sentences, from which roughly 1.5 million single-quiz question training examples were derived.  
 Question: What is the size of the dataset?

Answer:
300,000 sentences with 1.5 million single-quiz questions


