Implementation Addendum A URM-L0 Validator Profile and Reference Serialization (Non-Normative, Informative)

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Authors: M. L. Simpson
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Abstract

Implementation Addendum A: URM-L0 Validator Profile and Reference Serialization provides a non-normative, illustrative validator profile for the URM-L0 lexical core defined in URM: A Lexicon of Expression. The addendum formalizes a minimal, language-agnostic interchange format for URM-L0–normalized statements and a small set of mandatory well-formedness checks that a conformant validator must enforce. It is intended to make the abstract typing rules of the lexicon concretely implementable for tools and AI systems, without prescribing algorithms, execution engines, or optimization strategies. Specifically, this document defines: A reference JSON shape for URM-L0 statements, expressed as ordered sequences of typed tokens and explicit boundary elements. A complete Meta schema matching the lexicon’s L0 tags (role, scale, closure, persistence, record, regime, admissibility, lifecycle, agentive). A concise set of well-formedness rules (WF-1–WF-6) that enforce subject-free closure, prevent anthropomorphic or teleological formulations, and require explicit boundaries for cross-regime statements. Suggested validator error codes to support interpretable and debuggable implementations. Minimal illustrative examples, including both single-regime and mixed-regime statements with explicit Store-level boundaries. This addendum is non-normative and informative. All normative definitions, grammatical rules, and authority reside in the URM-Lexicon specification. The addendum does not constitute a required or authoritative implementation and imposes no obligation to adopt its mechanisms. The document makes no empirical claims and introduces no new physics. It is intended as a practical bridge between the URM-L0 language specification and real-world tooling, such as validators, linters, and AI ingestion pipelines that require explicit semantic well-formedness checks prior to reasoning.

Fields of Study & Subjects

Natural Language Processing Techniques Logic programming and type systems Model-Driven Software Engineering Techniques

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
3 January 2026