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d02622b
Auto-sync from demo at Wed Oct 29 12:31:26 UTC 2025
Browse files
graphgen/utils/calculate_confidence.py
CHANGED
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@@ -61,8 +61,8 @@ def _normalize_yes_no(tokens: List[Token]) -> Dict[str, float]:
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{"yes": 0.8, "no": 0.2}
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Among them, "yes" and "yeah" are synonyms for "yes",
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while "no" and "nope" are synonyms for "no".
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If
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"""
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yes_syno = {
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# English yes synonyms
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@@ -126,17 +126,23 @@ def _normalize_yes_no(tokens: List[Token]) -> Dict[str, float]:
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yes_prob = 0.0
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no_prob = 0.0
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for tok in tokens:
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t = tok.text.lower().strip()
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if t in yes_syno:
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yes_prob += tok.prob
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elif t in no_syno:
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no_prob += tok.prob
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def yes_no_loss_entropy(
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{"yes": 0.8, "no": 0.2}
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Among them, "yes" and "yeah" are synonyms for "yes",
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while "no" and "nope" are synonyms for "no".
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If no "yes" or "no" synonyms are present, it will be judged as uncertain.
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An uncertain result will also be considered as opposite to the ground truth.
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"""
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yes_syno = {
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# English yes synonyms
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yes_prob = 0.0
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no_prob = 0.0
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uncertain_prob = 0.0
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for tok in tokens:
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t = tok.text.lower().strip()
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if t in yes_syno:
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yes_prob += tok.prob
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elif t in no_syno:
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no_prob += tok.prob
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else:
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uncertain_prob += tok.prob
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total = yes_prob + no_prob + uncertain_prob
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return {
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"yes": yes_prob / total,
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"no": no_prob / total,
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"uncertain": uncertain_prob / total,
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}
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def yes_no_loss_entropy(
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