Idioms and proverbs (òwe) are central to Yorùbá discourse, yet computational Yorùbá NLP has concentrated on compositional tasks, leaving non-compositional expressions largely unaddressed. This study presents YorùbáÒwe, a publicly deployed web application for bidirectional Yorùbá↔English idiom and proverb translation. Its engine combines input normalization, sliding-window proverb detection, exact lexicon matching, near-match retrieval, rule-based context disambiguation, and word-level fallback. The engine's production source code was evaluated directly through a multi-layer evaluation. An initial evaluation against a 13-entry seed lexicon traced every Yorùbá-side miss (69.23% exact-match recall) to a hard-coded 12-token segmentation ceiling. The lexicon was then expanded to approximately 578 entries from a 568-pair Yorùbá–English proverb corpus, which was divided deterministically (80/20, random seed 42) into a 454-record Development/Lexicon Set and a 114-record Held-Out Test Set. All 13-unit tests passed, and the production build succeeded. On the Development/Lexicon Set the system retrieved the matching entry for 451/454 records (99.34% exact-match rate) and handled 806/818 controlled variants (98.53%); these figures describe lexicon-supported behavior, not general translation accuracy. On the Held-Out Test Set, evaluated with the held-out entries removed from the lexicon, reference-overlap scores were very low (BLEU 0.26, chrF 6.64, ROUGE-L F1 6.41; 0/114 exact textual matches), whereas a ChatGPT baseline on the same 114 records scored BLEU 38.42, chrF 58.77, and ROUGE-L F1 66.00 (4/114 exact textual matches). These metrics measure similarity to a single reference translation and do not establish translation quality. A human evaluation of 20 selected proverbs by three evaluators (60 judgments) gave mean ratings of 4.72/5 for meaning preservation, 4.72/5 for English naturalness, and 4.83/5 for cultural appropriateness, with 59/60 (98.33%) judged acceptable; an earlier 77-respondent evaluation of the 13 seed entries is also reported. YorùbáÒwe is therefore characterised as a lexicon-based, retrieval-oriented system whose coverage depends on its stored proverb knowledge.

Yorùbá language; idiom translation; proverb translation; òwe; natural language processing; multiword expressions; low-resource language; rule-based lexicon matching; web-based system; held-out evaluation; LLM baseline; human evaluation.