The words "bank," "river," and "finance" are projected into a 2D vector space. If "bank" is closer to "finance" than "river," what does this imply about the training corpus?

Question

Answer

c.  Laplace smoothing was applied

Answer

a.  The embedding model used a small window size

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b.  The word bank is polysemous

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d.  The corpus contains more financial documents than geographical texts.

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The words "bank," "river," and "finance" are projected into a 2D vector space. ...

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