The Manifesto of Vera Semantica

Version: 1.0 · Date: 1/3/2026

Fundamental Idea of the Initiative and Its Mission

The Semantic Representation of Law (SRP) initiative is the result of many years of conceptual development aimed at building a new legal system based on formal methods of knowledge representation. The starting point for this endeavor was a series of scientific reflections addressing highly practical issues.

Law, as one of the fundamental pillars of any community, guarantees the stability and predictability of societal functioning. Legal norms, which regulate nearly all domains of life, establish the framework within which individuals, institutions, states, and organizations operate. Consequently, a fundamentally important issue is not only compliance with the law—an obvious requirement—but also the interpretation of legal norms.

The quality of legal norms expressed in natural language is far from perfect. Due to linguistic inaccuracies in drafting provisions and discrepancies between the grammatical formulation of norms and the purposes they are intended to achieve, it becomes necessary to engage in the process known as legal interpretation. This process aims to determine the correct meaning of legal norms embedded in legal provisions and consists of a multi-stage set of highly complex operations.

The correct interpretation of legal provisions is achieved through interpretative directives of the first or second order. Interpretations may differ in binding force depending on the authority performing them, leading to distinctions between:

  • authentic interpretation
  • legal interpretation
  • operational interpretation
  • doctrinal interpretation

Furthermore, legal interpretation can be conducted using various methods, which are directly relevant to the SRP initiative.

  • Linguistic (grammatical) interpretation – syntactic and semantic analysis of words, phrases, punctuation, and linguistic structures
  • Teleological interpretation – based on the purpose of a norm
  • Systemic interpretation – based on the position within the legal system
  • Historical interpretation – based on historical context (primarily academic use)

Equally important for SRP is the distinction between:

  • declarative interpretation
  • extensive interpretation
  • restrictive interpretation

The Problem of Natural Language in Law

Even in this simplified presentation, the formulation and interpretation of legal norms emerge as highly complex processes, sensitive to imperfections both in human actors and—most critically—in the medium of representation itself, namely natural language.

Law constitutes a form of knowledge expressed through norms of behavior:

  • obligations
  • prohibitions
  • permissions
  • duties

The problem of ambiguity in natural language is widely recognized and well-established in scientific discourse. At its core lies the distinction between:

  • terms (lexical units)
  • concepts (mental constructs)

Concepts are inherently abstract and difficult to precisely capture, as they exist within the human mind and are defined through relationships with other concepts. Terms, on the other hand, are linguistic expressions that operate within the communicative layer, enabling information transfer.

Communication Process

Communication via natural language requires a two-stage translation process:

  1. Encoding
    Transforming mental constructs (ideas, rules, facts) into linguistic expressions

  2. Decoding
    Interpreting linguistic expressions back into conceptual structures

Understanding natural language involves:

  • grammatical parsing (subject, predicate, object, etc.)
  • semantic interpretation (mapping terms to concepts)

Sources of Errors

At each stage, significant errors may occur:

  • incorrect grammatical parsing
  • ambiguities in expression
  • misalignment between terms and concepts

These issues stem both from human limitations and the inherent imperfections of natural language itself.

Ambiguity

Ambiguity is particularly problematic:

  • One term → multiple concepts
    e.g., “lock”

  • One concept → multiple terms
    e.g., “car,” “vehicle,” “automobile”

Stylistic variation—often desirable in literary contexts—further reduces precision. In technical domains, such variation can lead to semantic inconsistencies (e.g., confusing “code” with “cipher” in cryptography).

Consequences for Legal Systems

Law should ideally be unambiguous—every recipient should interpret it in the same way. This requirement is fundamental to legal certainty but is inherently unattainable when relying solely on natural language.

As a result:

  • multiple interpretations of the same law are common
  • legal uncertainty arises
  • erroneous judicial or administrative decisions occur
  • public trust in institutions is undermined

Legal interpretation attempts to mitigate these issues but remains grounded in natural language and human reasoning, and therefore cannot fully eliminate them.

The SRP Concept

Years of research into these challenges, combined with advances in knowledge representation, have led to a novel and highly coherent concept: Semantic Representation of Law (SRP).

The core idea of SRP is the translation of legal content expressed in natural language into a formal Knowledge Representation Language (KBL) with:

  • well-defined grammar
  • explicitly defined semantic roles

Three Pillars of SRP

1. Translation

Converting legal norms expressed in natural language into formal expressions in a knowledge representation language.

2. Ontology Development

Constructing:

  • a foundational ontology
  • a domain-specific legal ontology

Ensuring unambiguous semantics of concepts.

3. Semantic Executor

Building a reasoning engine that:

  • performs semantic propagation
  • executes logical inference
  • generates unambiguous conclusions

Based on:

  • legal provisions
  • ontologies
  • representations of real-world situations

Knowledge Representation and Reasoning

A key requirement is the development of a knowledge representation language with:

  • high semantic capacity
  • high flexibility

Legal statements are decomposed into grammatical structures and transformed into formal expressions centered around predicates representing:

  • actions
  • properties
  • relations
  • states
  • operators

Concepts are assigned well-defined roles:

  • predefined (fixed semantics)
  • dynamically defined (contextual)

Advanced Mechanisms

The framework enables:

  • multidimensional semantic spaces
  • encapsulation (scoping of rules and facts)
  • temporal reasoning
  • Alethic – necessity, possibility
  • Epistemic – knowledge, belief
  • Deontic – obligations, prohibitions
  • Doxastic – belief systems