Definition: 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: We address this tension by training vector space models to represent the data, in which each unique word in a large corpus is represented by a vector (embedding) in high-dimensional space. The geometry of the resulting vector space captures many semantic relations between words. We address this tension by training vector space models to represent the data, in which each unique word in a large corpus is represented by a vector (embedding) in high-dimensional space. The geometry of the resulting vector space captures many semantic relations between words.
Question: Do they model semantics
Output:
Yes