Certify Schleicher's fable from frozen Phi - #696
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Rebuild the fable as four source-aligned units, derive its English in isolated contexts, and record D107 with exact source and digest evidence. The repaired opening now distinguishes all three horses explicitly.
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Summary
This certifies Schleicher's fable as the fourth translation completed under Phi's isolated two-phase process. The page is rebuilt as four aligned units, its natural English comes only from the frozen Phi, and D107 records the evidence in the generated certification ledger.
The new unit boundaries keep each continuing speech inside one quote frame. They also place all three horses and their work inside the proposition seen by the sheep, separate the person's ownership from the use of the wool, and recall the destination field explicitly. No root, module membership, registered compound, function word, or grammar rule is added.
Translation process
ta kaloraphrases did not require three distinct horses.ta shao kalorafor the exact group andnu ta,nu wi, andnu ta shaofor its three members. Fresh source-blind contexts then derived and independently audited the repaired unit.dec1e02503f0c9571c4da870a80d67610508efce1d8aa65cbd44d6e9641c3fca.774ed454c5d926c7dd45f10d56121cac4f77df54e0fdf73ee2d7a198ea0a4ef3.Reader-facing pass
The Humanizer and Phi voice review removed archival wording such as
preservesandrestoresfrom the notes. The replacement prose says what the clauses do in the scene: the first horse pulls, the second bears the load, and the third carries the person. A mechanical voice scan found no curly quotes, new em or en dashes, inflation vocabulary,-bearingforms, copula-avoidance phrases, or participial tails. The existing title dash remains protected project formatting.Repository records
texts/schleicher_fable.mdcertified in the machine-readable register and regenerate its readable ledger.Checks
python3 scripts/validate_examples.py: 1,301 entries, 0 errors, 0 warnings.python3 scripts/validate_sentences.py: 3,306 complete examples, 0 errors.python3 scripts/validate_sentences.py --paths texts/schleicher_fable.md --docs-only: 4 units, 0 errors.python3 scripts/test_sentence_validator.py: 25 tests passed.python3 scripts/test_translation_layers.py: 11 tests passed.python3 scripts/translation_process_status.py --check: 20 translations checked, 4 certified, 16 pending.python3 scripts/test_translation_process_status.py: 9 tests passed.python3 scripts/test_vocabulary_schema.py: 25 tests passed.python3 scripts/content_vocabulary_decisions.py --check: 81 batches and 280 decisions checked.python3 scripts/test_content_vocabulary_decisions.py: 8 tests passed.python3 scripts/test_name_forms.py: 20 tests passed.python3 scripts/audit_phonetic_neighbors.py --output /tmp/phonetic_neighbors_baseline_final.txtfollowed by an exact comparison with the tracked baseline: no difference.python3 scripts/build_site.py: complete site build passed.git diff --cached --check: passed before commit.The broader
python3 scripts/validate_sentences.py --docsmigration scan parses 5,531 examples and retains only its two recorded diagnostics indocuments/evaluation/narrative_test_corpus.md, PHS103 at line 46 and PHS115 at line 212. This PR adds neither.