StrictEN

StrictEN is a proposed framework for English language encoding and processing that prescribes formal, unambiguous rules for orthography, grammar, and punctuation. Originating in discussions within computational linguistics and language education, it aims to reduce irregularities and regional variation that can complicate natural language processing, data exchange, and automated translation.

The core idea of StrictEN is to provide a canonical set of forms and structures that yield consistent representations of English text. It emphasizes deterministic spelling norms for common words, explicit marking of morphemes and grammatical categories, and standardized punctuation. The framework can include guidance on word formation, disambiguation of homographs, and guidelines for sentence structure to improve parseability and machine readability.

Implementation in practice often appears as a combination of rule-based conventions and automated tooling. In educational settings, StrictEN-inspired curricula may use unambiguous spellings and controlled syntax to improve literacy and clarity. In software development and NLP research, researchers explore StrictEN as a baseline or target representation to simplify parsing, annotation, and multilingual alignment across corpora and systems.

StrictEN has attracted interest as a move toward more predictable English for machines, but it has faced criticism for potentially restricting natural usage, imposing prescriptive norms, and presenting learning challenges for diverse user groups. Critics argue that English variation is a feature, not a flaw, and that flexible approaches to language processing can coexist with robust conventions.

See also: controlled natural language, plain language, basic English, simplified English, constructed language concepts.