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]: Then we define the similarity between INLINEFORM7 and INLINEFORM8 by, DISPLAYFORM0 We note that the similarity metric defined above for sentences is equally applicable for n-gram retrieval.
Question: Which similarity measure do they use in their n-gram retrieval approach?
[A]: we define the similarity between INLINEFORM7 and INLINEFORM8 by, DISPLAYFORM0

[Q]: Overall, this resulted in a total of 34,432 user conversations. Together, these users gave Gunrock an average rating of 3.65 (median: 4.0), which was elicited at the end of the conversation ("On a scale from 1 to 5 stars, how do you feel about talking to this socialbot again?").
Question: What is the sample size of people used to measure user satisfaction?
[A]: 34,432 user conversations

[Q]: I also performed several case studies. I obtained document embeddings, in the same latent space as the topic embeddings, by summing the posterior mean vectors INLINEFORM0 for each token, and visualized them in two dimensions using INLINEFORM1 -SNE BIBREF24 (all vectors were normalized to unit length). The state of the Union addresses (Figure FIGREF27 ) are embedded almost linearly by year, with a major jump around the New Deal (1930s), and are well separated by party at any given time period.
Question: What is an example of a computational social science NLP task?
[A]:
Visualization of State of the union addresses