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b2e9550 0842763 b2e9550 0842763 b2e9550 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 | """Claim-schema aware deterministic numeric validation."""
from __future__ import annotations
import re
from copy import deepcopy
from numeric_core import validate_numeric
_EXACT_SPAN_KINDS = {"frequency", "effect_size"}
def _norm(value: str) -> str:
return re.sub(r"\s+", " ", str(value or "")).strip().casefold()
def validate_claim_numbers(
claim_text: str,
evidence_text: str,
numeric_facts: list[dict],
*,
relative_tolerance: float,
) -> tuple[str, list[dict], list[str]]:
facts = deepcopy(numeric_facts)
contains_number = bool(re.search(r"\d", claim_text)) or bool(facts)
if not contains_number:
return "not_applicable", facts, ["The claim contains no numeric assertion."]
full_result = validate_numeric(
claim_text,
evidence_text,
rel_tol=relative_tolerance,
)
reasons: list[str] = []
all_ok = bool(full_result.get("numeric_ok"))
for fact in facts:
raw_text = str(fact.get("raw_text") or "")
kind = str(fact.get("kind") or "")
raw_present = bool(raw_text) and _norm(raw_text) in _norm(evidence_text)
if kind in _EXACT_SPAN_KINDS:
fact_ok = raw_present
else:
fact_result = validate_numeric(
raw_text,
evidence_text,
rel_tol=relative_tolerance,
)
fact_ok = raw_present and bool(fact_result.get("numeric_ok"))
fact["status"] = "validated" if fact_ok else "conflicted"
fact["correction"] = None
if not fact_ok:
all_ok = False
reasons.append(
f"Numeric fact '{raw_text or kind}' is absent from or inconsistent with the source quote."
)
if all_ok:
reasons.append("All numeric assertions match the exact source quote; no correction was applied.")
return "validated", facts, reasons
reasons.append("At least one numeric assertion is unsupported or inconsistent; silent correction is forbidden.")
return "conflicted", facts, reasons
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