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: To study the lexical and semantic diversities of responses, we performed three analyses. First, we aggregated all worker responses to a particular question into a single list corresponding to that question. Second, we compared the diversity of individual responses between Control and AUI for each question. To measure diversity for a question, we computed the number of responses divided by the number of unique responses to that question. We call this the response density.  
 Question: How was lexical diversity measured?

A: By computing number of unique responses and number of responses divided by the number of unique responses to that question for each of the questions
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Q: 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?

A: Precision, Recall and INLINEFORM0 score
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Q: Different from scaled dot-product attention, Gaussian-masked directional attention expects to pay attention to the adjacent characters of each positions and cast the localness relationship between characters as a fix Gaussian weight for attention. We assume that the Gaussian weight only relys on the distance between characters. 
 Question: How does Gaussian-masked directional multi-head attention works?

A:
pays attentions to adjacent characters and casts a localness relationship between the characters as a fixed Gaussian weight assuming the weight relies on the distance between characters
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