Question: When using contextual embeddings from a model like GPT , how would the word right in Turn right at the corner differ from He

When using contextual embeddings from a model like GPT, how would the word "right" in "Turn right at the corner" differ from "He has the right to vote"?
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The embedding remains the same since "right" is the same word.
The embedding is slightly altered due to sentence length.
The embedding is based on the frequency of "right" in the training corpus.
The embedding changes based on the different contexts of usage.

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