ifwords

Ifwords is a theoretical construct in computational linguistics and rule-based AI for expressing conditional logic in natural-language form. It serves as an intermediate, human-readable notation that can be translated into machine-executable rules, decision trees, or templates. The term appears in academic discussions and experimental tooling as a minimal notation that anchors conditions to actions rather than program syntax.

The core form is a conditional with an if-clause and a then-clause, optionally followed by an else-clause. A canonical template is: If [condition], then [action], else [alternative]. Variants support conjunctions, negation, and nested conditionals, and they can be mapped to logical formulas or production rules.

Ifwords is intended as a bridge between domain experts and developers, aiding specification gathering, domain modeling, and rapid prototyping. It is commonly explored in tutorials and lightweight DSLs that translate natural-language-like conditionals into executable rules for chatbots and decision-support systems.

Critics note potential ambiguity when natural language is used without formal disambiguation, and warn that overreliance on natural-language glosses can hinder precise machine interpretation. Proponents argue that it lowers entry barriers and speeds iteration by preserving human readability.

See also: conditional statement, production rule, domain-specific language, natural language processing.