kami
e8941d8ceb
_annotate_speaker_methods stamped `tail`, the highest-trust provenance, on any line whose speaker matched a present local_id, at gemma's confidence of 1.0. No balloon was read. Three of three sampled two-character panels had the speakers swapped, so a multi-character guess is now dropped to unknown, and a solo-panel guess is kept as model_solo at 0.7. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2.6 KiB
Speaker attribution and cast names
Settled 2026-08-11 from the quality cross-check of job 778297bc
(JOURNAL.md, caveats/speaker-attribution.md). No GPU work ran and no pipeline run was executed
after the change. Both claims rest on source and on the CPU-only self-checks named below.
Files: worker_vision.py on workpc, correctness.py and test_script_verify.py in the homesrv
orchestrator (/mnt/server/home/kami/docker-apps/manga-infra/orchestrator/).
A model guess is never labelled tail
Closed. speaker_method names how a speaker was established, and nothing may claim geometry it did
not read. _annotate_speaker_methods stamped tail, the highest-trust label, on any line whose
speaker matched a local_id present in the panel, keeping gemma's confidence of 1.0. No balloon was
ever consulted.
Evidence: three of three sampled two-character panels had both speakers swapped
(caveats/speaker-attribution.md#tail-is-not-geometry). 31 of 81 speech lines carried tail with two
or more characters present.
The label is gone. With two or more characters present the guess is dropped: speaker becomes
unknown, confidence 0.0, method unknown. With one character present the claim equals the solo
backstop, so it is kept as model_solo at confidence 0.7. Grounded som_face and solo_prior rows are
untouched, because the function still skips any row that already carries a method.
Forbids: minting a provenance label for evidence that was not read, and shipping a multi-character
attribution as truth before balloon geometry exists.
Check: python worker_vision.py, the crowd/lone cases.
Cost: the named-speaker share will fall. The 30% headline was measured on attributions the sample says are wrong, so the lower number is the first honest one.
Cast names enter the verifier tokenized
Closed. verify_script compares single capitalized tokens, so every allowed name must be present as
tokens. allowed was built from cast_names verbatim, which put "choi haeseon" in the set as one
string while the checker looked up Choi and Haeseon separately.
Evidence: the script stage failed at 87/116 on job 778297bc. 28 of the 29 lost beats cite
unsupported-proper-noun: ['Choi', 'Haeseon']. A one-word name such as Seonho always passed, which
is why this survived the Phase 1 verifier work
(decisions/audit-phase1.md#verifier-false-positives).
Forbids: adding any future allow-list to verify_script as whole strings.
Check: pytest test_script_verify.py, test_multiword_cast_name_is_supported.