Completing the Analogy

A word-embedding model answers the analogy paris is to france as tokyo is to ___ by building the target vector

$\vec t = \vec{\text{france}} - \vec{\text{paris}} + \vec{\text{tokyo}}$

and returning the candidate whose embedding has the highest cosine similarity with $\vec t$.

The three known words:

The four candidates:

Which candidate does the model return?