1. Definition

A semantic structure that is interpreted within Pipeline of Ontology (PpoO) and processes the context of an RLg-phrase and an RLg-theme within the RLg-architecture (RLgA).

2. Theoretical Foundations

A CsO is discovered only through the execution of a preceding CsO within the Pipeline of Ontologies (PpoO). The verb CsO discovers and starts the SVV-CsO. The SVV-CsO discovers the next CsO based on the SR-description of the phrase and/or contextual data. Each subsequent CsO discovers the next one according to the discovery rules encoded in its own construction. Thus, CsOs are not discovered directly from the phrase; they are discovered sequentially, each by the preceding CsO.

3. Functionality

CsO processes data submitted to it, as well as data within the context of the current phrase and the context of the current topic. Each CsO contains executable rules that know where the identification data of the next CsO is located and how to work with that data. Based on these rules, the currently executed CsO determines which CsO must be started next and initiates its execution. Through this mechanism, the PpoO is assembled dynamically as a sequence of CsOs, each activated according to the identification logic encoded in its construction.

4. Types of CsOs

A. Verb CsOs

• Self-identify through the grammatical forms of the verb
• Discover the SVV-CsO based on the combination of the verb and the SR-description
• Contain discovery data enabling them to identify the correct SVV-CsO

B. SVV CsOs

• Identified and started by the preceding Verb CsO
• Discover the next CsO based on SR-pairs
• Contain discovery data and rules specifying which CsOs they can discover

C. Computational CsOs

• Identified by the preceding SVV-CsO
• Discover the next CsO based on phrase and theme context
• Contain discovery data and rules for context-based discovery

D. Thematic CsOs

• Self-identify through thematic word sets
• Discover next CsOs based on SR-pairs and/or contextual data
• Contain discovery data and rules depending on thematic specialization

5. Ownership

All components, derivative works and implementations of PpoO as a semantic construction are owned by Inato Ltd.

6. Public vs Proprietary IP

7. Licensing

UPI may be used under:

• Academic License — non-commercial research
• Commercial License — integration, deployment, product development

Restrictions: no copying, extraction or reconstruction of proprietary implementation details.

1. Definition

Multi-verb phrase (MVPh) in the Root Language architecture (RLgA) is a type of phrase represented as pairs consisting of a word and its Semantic Role (SR), which contains more than one verb SR-pair.

2. Components and Theoretical Foundations

An MVPh is composed of:

• Semantic Role pairs (SR-pairs) — each consisting of a word and its assigned semantic role.
• Multiple verb SR-pairs — the defining characteristic of MVPh.

The theoretical foundation of MVPh is based on the principle that phrases containing multiple verbs require non-linear semantic interpretation, where the relationships between verbs, roles and contextual dependencies cannot be resolved through the standard single-verb processing pipeline.

3. Functionality

The interpretation of a Multi-Verb Phrase (MVPh) in the Root Language architecture (RLgA) differs fundamentally from the interpretation of a simple phrase. A simple phrase contains a single verb and is processed dynamically through the phrase context, which ensures traceability because the phrase processing has no static definition.

An MVPh contains more than one verb and therefore cannot be interpreted directly. Instead, its semantic description is decomposed into multiple simple Semantic Role descriptions, each containing exactly one verb. Simple RLg-phrases are constructed from these simple SR-descriptions and are arranged after the decomposed MVPh within the currently processed topic.

As a result, the content of the theme is unified into a sequence consisting only of simple RLg-phrases, enabling consistent processing through the standard RLgA mechanisms. This decomposition-based processing is the defining functional characteristic of MVPh and distinguishes it from all other phrase types within RLgA.

4. Ownership

All components, derivative works and implementations of PpoO as a semantic construction are owned by Inato Ltd.

5. Public vs Proprietary IP

6. Licensing

UPI may be used under:

• Academic License — non-commercial research
• Commercial License — integration, deployment, product development

Restrictions: no copying, extraction or reconstruction of proprietary implementation details.

1. Definition

The Pipeline of Ontologies (PpoO) is a semantic processing mechanism used within the RLg-architecture during the interpretation of an RLg-phrase. PpoO represents a dynamically assembled sequence of Common Sense Ontologies (CsOs), each contributing specialized interpretation logic. The pipeline is executed as part of the RLg-phrase processing workflow and provides a unified mechanism for semantic interpretation.

2. Components and Theoretical Foundations

PpoO has no predetermined or static composition. Its structure emerges dynamically from the interpretation logic embedded in each CsO. Each CsO may specify the initiation of subsequent CsOs, resulting in a self-assembled semantic pipeline. The theoretical foundation of PpoO is the principle of dynamic semantic interpretation, where the meaning of a phrase is constructed through sequential execution of CsO-based interpretation units.

3. Functionality

During execution of PpoO, the following operations are performed:

• A. Interpretation of CsO logic — processing the semantic content provided by Semantic Roles (SR) within the RLg-phrase context and the RLg-theme context.
• B. Dynamic discovery and initiation of subsequent CsOs — if specified by the currently interpreted CsO.
• C. Maintenance of semantic continuity — ensuring consistent interpretation across the dynamically assembled sequence of CsOs.

4. Ownership

All components, derivative works and implementations of PpoO as a semantic construction are owned by Inato Ltd.

5. Public vs Proprietary IP

6. Licensing

PpoO may be used under:

• Academic License — non-commercial research
• Commercial License — integration, deployment, product development

Restrictions: no copying, extraction or reconstruction of proprietary implementation details.

1. Definition

The Root Language architecture (RLgA) defines a set of semantic component types, their connectivity and operational principles required for unified representation of actions, roles, processes and contextual dependencies. RLgA enables integration between neuro-AI and symbolic AI by providing a semantic transformation layer that converts Natural Language (NL) output into RLg-semantic structures.

RLgA defines semantic roles (SR) as the foundation for constructing action-interpretation mechanisms, enabling consistent representation of processes and contextual dependencies. After conversion, the information is represented as a Unified Knowledge Graph Representation (uKGR) and transferred into the symbolic AI's Unified Knowledge Graph (uKG) environment, where it is processed as graph-organized data.

RLgA is a semantic superstructure built on top of UPI and uKG, providing the semantic structures required for interpreting actions, roles and processes in a unified neuro-symbolic workflow.

2. Components and Functionality

RLgA is organized into three semantic levels, defined by their correspondence to natural language: Scene, Theme, and Phrase. These levels are represented in the uKG environment through the constructs RLg-scene, RLg-theme, and RLg-phrase.

Scene Level

Scene-level processing is structured as a sequential interpretation of the themes contained within a scene. A scene context is maintained during processing, spanning a unified time interval that governs the interpretation of all themes within the scene.

Theme Level

Theme-level processing is structured as a sequential interpretation of the phrases contained within a theme. A theme context is maintained, spanning a time interval dedicated to processing the phrases within the theme. This interval is contained within the contextual time interval of the scene to which the theme belongs.

Phrase Level

Phrase-level processing depends on whether the phrase contains:

• a single verb (simple phrase), or
• multiple verbs (multi-verb phrase, MVPh).

An MVPh requires specialized interpretation logic and is covered by the Multi-Verb Phrase Intellectual Property License.

A simple phrase is represented as semantic pairs consisting of a word and its Semantic Role (SR). A phrase context is maintained to ensure traceability of the interpretation process. This processing is dynamically assembled through the interpretation of semantic constructs called Common Sense Ontologies (CsO), each containing specialized interpretation logic.

CsO is covered by the Common Sense Ontologies Intellectual Property License.

The dynamically assembled sequence of CsOs constitutes a Pipeline of Ontologies (PpoO), which follows a specific assembly logic. Pipeline of Ontologies is covered by the Pipeline of Ontologies Intellectual Property License.

3. Theoretical Foundations

• The idea of the three RLg levels is developed in the article Root Language and Machine Education.
• The concept of a reference time interval is developed in the article Time and space in the Unified Knowledge Graph environment.

4. Ownership

All components, derivative works and implementations of RLgA are the property of Inato Ltd.

5. Public vs Proprietary IP

6. Licensing

RLgA may be used under:

• Academic License — non-commercial research
• Commercial License — integration, deployment, product development

Restrictions: no copying, extraction or reconstruction of proprietary implementation details.

1. Definition

A Semantic Verb Version (SVV) in the Root Language architecture (RLgA) is a semantic verb sign that is not present in the phrase, but is derived from the verb in its grammatical form and from the Semantic Role (SR) description of the phrase. SVV is represented in RLgA through a Common Sense Ontology (CsO) and participates in the Pipeline of Ontologies (PpoO) of the phrase as a control element. SVV is defined as a separate Intellectual Property component within the RLgA framework.

2. Theoretical Foundations

SVV is determined by:

• the verb in its grammatical form, as it appears in the phrase
• the SR-description of the phrase, which defines the semantic relations between the words

SVV is a semantic sign with verb meaning, and its CsO-representation encodes the semantic interpretation of the verb in the context of the phrase.

3. Functionality

The functionality of CsOs in RLgA and PpoO includes:

• Verb CsO (first CsO in PpoO) — The verb is represented by a CsO that initiates the PpoO of the phrase.
• SVV-CsO (second CsO in PpoO) — The SVV is represented by a CsO that follows the verb CsO and acts as a semantic control element.
• SVV-driven PpoO assembly — The SVV-CsO selects the next CsO in the pipeline, guiding the dynamic assembly of the PpoO based on the semantic interpretation of the verb and the SR-description of the phrase.

SVV therefore acts as the semantic driver of the PpoO of the phrase.

4. Ownership

All components, derivative works and implementations of SVV as a semantic construction are owned by Inato Ltd.

5. Public vs Proprietary IP

6. Licensing

UPI may be used under:

• Academic License — non-commercial research
• Commercial License — integration, deployment, product development

Restrictions: no copying, extraction or reconstruction of proprietary implementation details.

1. Definition

The Unified Knowledge Graph (uKG) environment constitutes a UPI-superstructure containing tools for creating and processing unified semantic constructs based on graph-organized objects. uKG extends the UPI environment by introducing unified rules for semantic graph organization. The semantic representation of the objects complies with the regulations established in the UPI semantic definitions.

2. Subject of Unification and Theoretical Foundations

The scope of the unification of uKG nodes and arcs is determined as follows:

A. Types of data subject to unification contained in the uKG nodes

• Textual name of the node
• Textual description of the conceptual meaning
• Logical identifier — ensures unique identification of nodes participating in multiple uKG environments
• Physical identifier — ensures unique identification within the uKG environment where the node is created
• Author and timestamp metadata
• Clarifying data — data representing the thematic essence of a given node; consequently, their composition varies for nodes with different thematic orientations

B. Types of data subject to unification contained in the uKG arcs

• Physical identifier — ensures unique identification within the uKG environment where the arc is created
• Specialization of an arc represented through conceptual meaning of data, processes or direct by concept definition
• Sequential number for arcs originating from the same node
• Author and timestamp metadata
• Clarifying data — data representing the thematic essence of a given arc; consequently, their composition varies for arcs with different thematic orientations

uKG is built on the theoretical framework defined in the Unified Knowledge Graph.

3. Functionality

uKG provides tools for:

• Creating unified semantic constructs that serve as one of the elements for achieving semantic interoperability within the uKG environment
• Achieving a high degree of reusability for software implementation components designed for semantic processing in uKG environment

4. Ownership

All components, derivative works and implementations of uKG as graph-organized data are the property of Inato Ltd.

5. Public vs Proprietary IP

6. Licensing

uKG may be used under:

• Academic License — non-commercial research
• Commercial License — integration, deployment, product development

Restrictions: no copying, extraction or reconstruction of proprietary implementation details.

1. Definition

UPI is a software environment built upon a Semantic Network-Based Architecture (SNBA). It contains a minimal set of semantic development tools and object models that enable the creation, processing and execution of semantic constructs. These tools rely on the semantic representation mechanisms defined in the UPI semantic definitions. The SNBA and UPI semantic definitions are theoretical works that provide the conceptual foundation for UPI but are not part of its proprietary implementation.

2. Components and Theoretical Foundations

UPI comprises:

• A software environment for semantic graph management and execution
• A minimal set of semantic development tools and object models
• A runtime capable of processing semantic constructs

UPI is built on the theoretical framework of:

• Semantic Network-Based Architecture (SNBA)
• UPI semantic definitions

3. Functionality

UPI provides tools for:

• Creating, editing and removing nodes and edges in the UPI semantic graph
• Visualizing semantic structures
• Embedding executable program code into graph elements
• Generating specialized semantic environments and conventional systems (workflow management, administrative processes, discrete manufacturing)

4. Ownership

All components, derivative works and implementations of UPI as a software environment are owned by Inato Ltd.

5. Public vs Proprietary IP

6. Licensing

UPI may be used under:

• Academic License — non-commercial research
• Commercial License — integration, deployment, product development

Restrictions: no copying, extraction or reconstruction of proprietary implementation details.