Author here. Some context that didn't fit the post.
Why I built it: English won the "world language" position by historical accident, and I kept noticing that almost none of its difficulty does communicative work — it's residue (spelling frozen by the printing press mid-vowel-shift, verbs that fossilized before the -ed rule generalized, articles that even advanced learners never master). I wanted to answer one narrow question rigorously: how simple could English be while still being English?
How it works: I started from the research (what learners actually struggle with, with sources), turned each pain point into a design target, and held every rule to the same acceptance bar — it must be statable without a hidden word list, and the spec's own examples must pass a mechanical sweep. That last part exists because my first design pass produced contradictions I only caught after building a linter that scans the World-English example text for abolished forms (an irregular verb, a "was", a "children") that leaked back in. Rules are not stable until they survive their own tooling.
Tech: static Astro site, tools in TypeScript/Bun. The translator is deliberately deterministic — it applies only the transforms it can prove from surface forms (verb regularization, plurals, banned words) and flags everything that needs part-of-speech or syntax (article deletion, tense changes) instead of guessing. There's also a reverse translator (WoE → standard English), a pronunciation renderer (respelling + IPA + audio via espeak-ng), and the whole thing ships as a Claude Agent Skill if you want an LLM to do the syntax-aware translation the deterministic tool won't.
The obvious limitation, stated plainly: nobody is going to adopt this, and it's not trying to be adopted. A century of prior art — Basic English, the spelling reform boards, Esperanto — is a graveyard, and there's a research page documenting exactly what each one tried and why it died. This is a design study. The output I care about is the map of where English's difficulty lives.
The most useful comment you can leave: pick one specific rule and tell me where it breaks. Every rule's spec records the problem it solves, the trade-off it accepts, and the alternatives it rejected — so "this whole idea is dumb" is less fun for both of us than "rule G2 collapses under anaphora, here's a sentence it can't handle."
ccarnino•1h ago
Why I built it: English won the "world language" position by historical accident, and I kept noticing that almost none of its difficulty does communicative work — it's residue (spelling frozen by the printing press mid-vowel-shift, verbs that fossilized before the -ed rule generalized, articles that even advanced learners never master). I wanted to answer one narrow question rigorously: how simple could English be while still being English?
How it works: I started from the research (what learners actually struggle with, with sources), turned each pain point into a design target, and held every rule to the same acceptance bar — it must be statable without a hidden word list, and the spec's own examples must pass a mechanical sweep. That last part exists because my first design pass produced contradictions I only caught after building a linter that scans the World-English example text for abolished forms (an irregular verb, a "was", a "children") that leaked back in. Rules are not stable until they survive their own tooling.
Tech: static Astro site, tools in TypeScript/Bun. The translator is deliberately deterministic — it applies only the transforms it can prove from surface forms (verb regularization, plurals, banned words) and flags everything that needs part-of-speech or syntax (article deletion, tense changes) instead of guessing. There's also a reverse translator (WoE → standard English), a pronunciation renderer (respelling + IPA + audio via espeak-ng), and the whole thing ships as a Claude Agent Skill if you want an LLM to do the syntax-aware translation the deterministic tool won't.
The obvious limitation, stated plainly: nobody is going to adopt this, and it's not trying to be adopted. A century of prior art — Basic English, the spelling reform boards, Esperanto — is a graveyard, and there's a research page documenting exactly what each one tried and why it died. This is a design study. The output I care about is the map of where English's difficulty lives.
The most useful comment you can leave: pick one specific rule and tell me where it breaks. Every rule's spec records the problem it solves, the trade-off it accepts, and the alternatives it rejected — so "this whole idea is dumb" is less fun for both of us than "rule G2 collapses under anaphora, here's a sentence it can't handle."
Rules on one page: https://worldenglish.tugulab.org/rules/learner-grammar/ Translator: https://worldenglish.tugulab.org/translate Prior art / research: https://worldenglish.tugulab.org/research/ Code (MIT) + specs (CC BY): https://github.com/clacladev/world-english