Question regarding semantic correctness of sentences

[rphlstck]

Excuse me if this is not the right venue to ask this question, but maybe your expertise could help me out!

Consider following candidates:
'My left ear hurts but my right eye is good'
and
'My left eye is good but my right ear hurts.'

Now, I calculate the BERTScore to my ground truth:
'My right ear hurts but my left eye is good.'

I would expect that the second sentence yields a greater BERTScore as it more correctly captures the underlying information of the ground truth sentence. However, this would require the score to operate on a higher abstraction than on the token level (right?).
Is there a way to adapt the BERTScore to achieve this? Or are you aware of a metric capable of capturing the meaning of a sentence?

These are the results I get:

Reference: My right ear hurts but my left eye is good.
Candidate:
My left ear hurts but my right eye is good.
microsoft/deberta-xlarge-mnli_L40_no-idf_version=0.3.12(hug_trans=4.33.2): P=0.966590 R=0.951585 F=0.959029
Candidate:
My left eye is good but my right ear hurts.
microsoft/deberta-xlarge-mnli_L40_no-idf_version=0.3.12(hug_trans=4.33.2): P=0.895558 R=0.891666 F=0.893608

This is my code:

from typing import List
from bert_score import score

def calc_score(refs: List, cands: List):
    (P, R, F), hashname = score(cands, refs, model_type='microsoft/deberta-xlarge-mnli', return_hash=True)
    print(f'Candidate:\n{cands[0]}')
    print(
        f"{hashname}: P={P.mean().item():.6f} R={R.mean().item():.6f} F={F.mean().item():.6f}"
    )

def sentence_ordering():
    '''
    Calculate the BERTScore for two sentences. 
    In the first sentence the meaning is altered by switching "left"/"right".
    In the second sentence the meaning is preserved but the order is switched.
    '''
    cands = ['My left ear hurts but my right eye is good.', 
             'My left eye is good but my right ear hurts.']
    refs = ['My right ear hurts but my left eye is good.']

    print(f'Reference: {refs[0]}')
    for cand in cands:
        calc_score(refs, [cand])

if __name__ == "__main__":
    sentence_ordering()

Note that ChatGPT3.5 will give following answer:
Prompt:

Which of the following sentences (`Sentence 1` or `Sentence 2`) more accurately contains the information provided in the `Ground truth`?

Sentence 1: 'My left ear hurts but my right eye is good.'
Sentence 2: 'My left eye is good but my right ear hurts.'
Ground truth: 'My right ear hurts but my left eye is good.'

Answer:

Sentence 2 more accurately contains the information provided in the Ground truth. It correctly represents the information about the right ear hurting and the left eye being in good condition.