Scope
Bootstrap Arabic (ar) LLM-assisted candidate translations.
Current audit
- workflow:
ar-empty-profile-bootstrap
- profile files exist but contain zero rows
- this is not a normal gap-fill workflow
Workflow
Follow docs/llm_translation_workflows.md and translation_workflows/candidate_workflows.json.
- first establish a canonical source-row inventory matching the Babelon schema
- generate Arabic candidate rows with Codex CLI /
gpt-5
- preserve exact HPO IDs, predicates, and source labels
- validate profile shape and row matching before apply
- triangulate with free review lanes where usable:
- OpenCode /
opencode/deepseek-v4-flash-free
- OpenCode /
opencode/mimo-v2.5-free
- add right-to-left text and punctuation checks
- apply only as
CANDIDATE
- keep
translation_type=LLM_ASSISTED_DRAFT
Conflict handling
Do not invent source rows from docs alone. If Arabic terminology differs between models, keep the more literal HPO candidate and document unresolved terms for human review.
Scope
Bootstrap Arabic (
ar) LLM-assisted candidate translations.Current audit
ar-empty-profile-bootstrapWorkflow
Follow
docs/llm_translation_workflows.mdandtranslation_workflows/candidate_workflows.json.gpt-5opencode/deepseek-v4-flash-freeopencode/mimo-v2.5-freeCANDIDATEtranslation_type=LLM_ASSISTED_DRAFTConflict handling
Do not invent source rows from docs alone. If Arabic terminology differs between models, keep the more literal HPO candidate and document unresolved terms for human review.