AI inside
The Forgotten Code: Validating a Century-Old Translation System with AI
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The study was conceived as a proof of concept (PoC) rather than a benchmark exercise. Its objective is to test, empirically and in a controlled manner, the operational validity of Federico Pucci’s interlingual method (1931):
- reconstruct the rule-based procedure he proposed,
- instrument contemporary large language models (LLMs) to execute that procedure on the same canonical excerpts Pucci used, and
- quantify the divergence between the resulting outputs and Pucci’s original translations.
The findings—consistently low average deviations on the target passages and replicability on additional language directions explored—indicate that it is the method that generalizes. As such, Pucci’s rules can plausibly operate as an explainable, symbolic component within a modern neuro-symbolic architecture.
The PoC is deliberately narrow in scope. It does not claim multi-genre or multi-language robustness. The experimental corpus is restricted to Pucci’s two canonical passages (Dante, it→fr; Voltaire, fr→it), because the sole question at stake is: Is Pucci’s 1931 procedure operational and replicable today? Within that frame, the answer is yes.
The study seeks a historical–conceptual “existence proof”—or proof of feasibility—showing that a pre-RBMT rule set can be instantiated a century later with traceability. To keep inference tight and attributable, the design uses:
1. Gold Reference (R). Pucci’s 1931 “mechanical” translations serve as the reference (R).They are not AI outputs; they are treated as the designated reference in distance calculations D(Ci→R).
2. Controlled Contrast (C₀/C₁).
- C₀: the LLM/NMT system without Pucci’s rules;
- C₁: the same system with Pucci’s rules explicitly enforced via instruction.
- ChatGPT: 20 deletions + 22 additions = 42 edits
- Claude: 20 + 19 = 39 edits
- Grok: 24 + 28 = 52 edits
- The PoC provides evidence of operability and replicability of Pucci’s rule set on the defined tasks. It does not claim broad generalization across genres, domains, or arbitrary language pairs.
- The inference is appropriately conservative: causal attribution is confined to the contrast tested.
- Broaden corpora (beyond the canonical excerpts) and extend to additional language pairs and registers;
- Run a pilot with human post-editing and contemporary automatic metrics (BLEU / chrF / METEOR) to assess practical and conceptual value at scale;
- Incorporate controls (placebo rules, further ablations) to stress-test attribution.
- activating the rules does not produce a stable effect (C₁ ≈ C₀);
- ablations fail to yield the expected error profiles; or
- the pipeline is not traceable (i.e., edits cannot be linked to specific rules, or the sequence cannot be replayed with the same result).
A pioneering rule-based mechanical translation system (precursor of modern RBMTs) was first presented in December 1929 by its inventor, Federico Pucci, who later published the full method in a book titled "Il traduttore meccanico ed il metodo per corrispondersi fra Europei conoscendo ciascuno solo la propria lingua: Parte I", in Salerno (Italy), in 1931. This study illustrates how AI breathes new life into the system of international keys and ideograms devised by Pucci to translate from/into any Romance language (at least as a first step). The methodology involves having the AIs retranslate, following Pucci's method, the two text excerpts originally translated in 1931 and clearly documented in his publication: a passage from Dante's La Vita Nuova, translated from Italian into French, and a passage from Voltaire's Zadig, translated from French into Italian. The result is notable: the two texts, translated 94 years apart using the same method--by Pucci in 1931 and by AIs in 2025--show a low average difference, with only minor variations observed. With Pucci's system thus validated, it became feasible to have the AIs reproduce the excerpts in English, Spanish, and German according to his method. The results were consistent, and Pucci--via Artificial Intelligence--was tasked with translating more modern and technical texts, thereby reviving, nearly a century later, an invention that had remained almost entirely unknown and never applied beyond its creator, now brought to wider attention and opened to possible experimentation. Such a demonstration would not only affirm Pucci's historical status but also place him among the precursors and intellectual contributors to machine translation, whose work merits examination alongside figures such as Troyanskij, Booth, and Weaver, with possible consequences for how the history of the field is understood.