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The judge now has to quote the passage it judges, and an opinion whose quote is not
there is dropped and said to be. The check is exact at word and number boundaries, so
"2 million" is not found in "1.2 million". The AVeriTeC eval can now show the judge
the NEIs too. It fixed 5 claims and broke none, but at p = 0.062 that is short of the
bar set beforehand, so the product does not do it.
Changed
- The judge's quote is checked, and shown. A
SUPPORTEDorREFUTEDopinion now
has to return the exact words from the passage that decide it, in a newquote
field. An opinion is dropped, with a note saying why, when its quote has no words,
when a part of it is shorter than two words, or when it is not in the passage it was
shown at word boundaries ("5 million" is not in "15 million"). The match folds case,
curly quotes, dashes and the minus sign, spaces, the fraction slash and invisible
characters such as the soft hyphen, and nothing else: a superscript stays a
superscript, and a sign or a percent is never trimmed....may elide the middle of
a quote as long as every part is in the passage, in order. The verified quote is
printed in the judge line,judge (<model>): SUPPORTED — "<quote>" — <rationale>,
and JSON gains aquotefield. AnNEIopinion asserts nothing and may quote
nothing. Cached opinions are now keyed by the passage they were checked against, and
those cached before this change are not served again: the next run asks.
Added
- AVeriTeC eval:
--judge-neiand--no-fallback(scripts/eval_averitec.py).
--judge-nei(requires--judge) also sends every read source whose verdict is NEI
to the judge, with the passage the models came closest to deciding on, and the
hypothetical column gains a second number in which those opinions vote too, with its
per-label counts, its wrong-way count beside the product's, and an exact McNemar test
against the product claim by claim. The report also counts opinions by model and kind
of escalation, and the ones the quote check dropped by reason.--no-fallback
(requires--judge) turns the judge's local fallback off for the run, so every
opinion is from the configured model. Both
flags get their own results file and report name. Measurement only: the product
still never sends an NEI to the judge.