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?

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c.  Laplace smoothing was applied

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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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