The Event Relationship Dependency Module (ERLDM)
governs how dependency
OOF™ Origin Open Foundation™
Independent Methodological Authority
Architecture Ecosystem: Structured Reality Standards™
Architecture Family: TREGA™ — Tax-Relevant Event Governance Architecture™
Parent Standard: TRERLS — Tax-Relevant Event Relationship Standard
Module: ERLDM — Event Relationship Dependency Module
Operational Layer: Event Relationship Dependency Governance Layer
Category: Governance & Enforcement
Subcategory: Tax-Relevant Event Governance
Type: Core Module
Governed Space: Event Relationship Dependency
Origin ID: TREGA-TRERLS-ERLDM-002
Version: 1.0
Status: Canonical · Open Standard
Effective Date: 1 September 2026
AI-Readable: Yes
Authority: OOF®
Protection: MIP® — Methodological Intellectual Property
Canonical Language: UCL — Universal Canonical Language
Canonical Definition
The Event Relationship Dependency Module (ERLDM) governs howdependency among already-identified Event Relationship Candidates
is established, distinguished, directed, qualified, and
represented within TRERLS.
ERLDM determines whether one governed event depends materially on
another event, whether the dependency is directional or mutual,
whether it is conditional, partial, structural, operational, or
value-related, and whether the dependency is sufficiently
established for further Event Relationship governance.
Its principal transition is:
Governed Event Relationship Candidate Set
↓
Event Dependency Governance
↓
Governed Event Dependency Structure
ERLDM does not determine event sequence, grouping, merge, split,
Event Identity, Event Boundary, or jurisdiction-specific tax
consequences.
The foundational distinction is:
Event Dependency ≠ Event Identity.
Operational Role
Events can be strongly related without being the same event.A payment may depend on an earlier purchase.
A refund may depend on an earlier settlement.
A machine execution may depend on a prior instruction.
A settlement may depend on several earlier transactions.
A later service event may depend on the completion of an earlier
operational event.
ERLDM provides the governance required to represent those
dependency structures without collapsing dependent events into
one event.
It also prevents the opposite error: assuming that two events are
independent merely because they were recorded separately.
Internal Module Flow
TRERLS operates through:ERLIM — Event Relationship Identification
↓
ERLDM — Event
Relationship Dependency
↓
ERLSM — Event Relationship Sequence
↓
ERLGM — Event Relationship Grouping
↓
ERLMM — Event Relationship
Merge & Split
↓
Governed Event Relationship Structure
ERLDM receives Relationship Candidates from ERLIM.
Its output is passed to ERLSM for sequence governance.
Operational Transition
The canonical transition is:Governed Event Relationship Candidate Set + Dependency Indicators
↓
Dependency Governance
↓
Governed Event Dependency Structure
ERLDM determines the dependency relationship among candidate
events without yet deciding their final sequence or group
structure.
Operational Space
ERLDM governs: dependency existence; dependency direction;unidirectional dependency; mutual dependency; conditional
dependency; partial dependency; structural dependency;
operational dependency; value-related dependency; execution
dependency; fulfillment dependency; settlement dependency;
reversal dependency; dependency strength; dependency
qualification; dependency uncertainty; dependency conflict;
dependency reconsideration; dependency continuity; and
dependency-specific traceability.
Operational Scope
ERLDM may govern dependencies across: commerce; payments;banking; ERP systems; accounting; supply chains; logistics;
marketplaces; digital platforms; blockchain; smart contracts;
digital assets; energy systems; industrial systems; AI agents;
autonomous machines; distributed systems; machine-to-machine
environments; cross-border operations; and other governed
economic infrastructures.
The dependency structure is technology-neutral.
Dependency Object
A Dependency Object is a governed representation of a dependencybetween two or more Tax-Relevant Events.
It identifies: the involved events; the direction of dependency;
the basis of dependency; the dependency condition where
applicable; the degree or extent of dependency; the current
governance state; and relevant uncertainty or conflict.
Dependency Object ≠ Event Identity.
Dependency Establishment
A dependency exists where one event materially relies on anotherevent for its occurrence, execution, completion, continuation,
settlement, reversal, or another governed function.
Dependency shall be established on governed information rather
than assumption.
Relationship Candidate ≠ Dependency by default.
Unidirectional Dependency
A dependency may operate in one direction.The canonical form is:
Event B depends on Event A
This does not automatically imply:Event A depends on Event B
Therefore:A
↓
B ≠ B
↓
A.
Direction must remain explicit.
Mutual Dependency
Two events may depend on each other.For example, two coordinated autonomous processes may each
require the other to complete a broader operation.
ERLDM may establish mutual dependency where supported.
However:
Mutual Dependency ≠ Single Event by default.
The events may remain independently formed and bounded.
Conditional Dependency
An event may depend on another event only if a governed conditionis satisfied.
Examples include: payment after delivery; refund after return;
release after approval; machine execution after authorization;
settlement after threshold completion.
ERLDM may represent the condition.
It does not govern authority or permission itself.
Conditional Dependency ≠ Authority Governance.
Partial Dependency
An event may depend only partially on another event.For example, a settlement may include several transactions but
only part of its value may depend on a specific earlier event.
ERLDM shall support partial dependency.
Partial Dependency ≠ Full Event Dependency.
Structural Dependency
Events may be structurally dependent within a broader operationalprocess.
One event may create a condition, state, or reference required
for another event to exist or proceed.
Structural Dependency ≠ Same Event Structure.
Structural dependence does not eliminate Event Independence.
Operational Dependency
An event may depend on another event for operational execution.Examples include: fulfillment depending on order acceptance;
machine execution depending on resource allocation; shipment
depending on production completion; settlement depending on
payment processing.
ERLDM may govern that relationship.
Operational Dependency ≠ Legal Dependency.
Value-Related Dependency
One event may depend on the value result of another event.For example: refund depends on earlier payment value; settlement
depends on accumulated transaction value; rebate depends on
earlier purchase volume; machine billing depends on measured
resource consumption.
ERLDM governs the dependency relationship.
TRVAS remains authoritative for the underlying Value Association.
Value Dependency ≠ Value Ownership.
Execution Dependency
A later event may require completion or execution of an earlierevent.
ERLDM may represent:
Execution of Event B depends on Event A
This does not determine chronological sequence in full.ERLSM remains authoritative for sequence.
Fulfillment Dependency
A fulfillment event may depend on an earlier commercial oroperational event.
The dependency may be strong even if fulfillment occurs much
later.
Time Distance ≠ No Dependency.
Settlement Dependency
Settlement events frequently depend on earlier payment,transaction, or value-related events.
One settlement may depend on: one event; several events; an Event
Group; or a larger Event Network.
Settlement Dependency ≠ Event Merge.
Refund Dependency
A refund event may depend on an earlier purchase, payment, orsettlement event.
ERLDM may govern that dependency without determining tax
adjustment.
Refund Dependency ≠ Tax Adjustment Determination.
Reversal Dependency
A reversal event usually depends on an earlier event that isbeing reversed or offset.
ERLDM may establish that dependency.
It does not determine whether the reversal is complete or partial
unless that dependency extent is materially governed.
Reversal Dependency ≠ Original Event Erasure.
Replacement Dependency
A replacement event may depend on an earlier failed or supersededevent.
ERLDM may preserve the dependency relationship.
Replacement Dependency ≠ Event Identity.
Continuation Dependency
A continuation event may depend on an earlier event for context,state, or operational progression.
ERLDM may represent that dependency.
Continuation Dependency ≠ Same Event Continuity by default.
TRECLS remains authoritative for continuity of one event.
Parent–Child Dependency
Some event structures may exhibit hierarchical dependency.
A child event may depend on a parent event without being absorbed
into it.
Parent–Child Dependency ≠ Event Ownership.
and:
Child Dependency ≠ Same Event.
One-to-One Dependency
One event may depend on one other event.The form is:
A
↓
B
where B depends on A.
One-to-Many Dependency
One event may create dependency for several later events.Example:
Event A
↓
Event B, Event C, Event D
This may occur in commerce, machine systems, or digital
platforms.
One Source Event ≠ One Dependent Event.
Many-to-One Dependency
One event may depend on several earlier events.Example:
Event A + Event B + Event C
↓
Event D
This is common in settlements, aggregation processes, machine
operations, and composite services.
Many Dependencies ≠ Event Merge by default.
Many-to-Many Dependency
Complex systems may produce networks where several events dependon several others.
ERLDM shall support such structures without forcing
simplification into one-to-one relationships.
Direct Dependency
A direct dependency exists where one event materially depends onanother without an intermediate governed event being required to
express the relationship.
Direct Dependency ≠ Stronger Legal Consequence by default.
Indirect Dependency
An event may depend on another through one or more intermediateevents.
Example:
A
↓
B
↓
C
Event C may indirectly depend on Event A.
ERLDM may represent indirect dependency where materially
relevant.
Indirect Dependency ≠ Irrelevant Dependency.
Immediate Dependency
A dependency may be immediate in the operational chain.This does not necessarily mean the events occur close in time.
Immediate Dependency ≠ Temporal Immediacy.
Deferred Dependency
A later event may depend on an event that occurred much earlier.For example, an annual rebate event may depend on purchases
throughout the year.
ERLDM shall support deferred dependency.
Dependency Condition
Where dependency is conditional, the condition shall berepresented separately from the event itself.
Examples may include: completion threshold; participant action;
system state; resource availability; prior payment; approval;
return; failure; or another governed condition.
Dependency Condition ≠ Event Identity.
Dependency Trigger
A specific occurrence may activate a dependency.ERLDM may preserve the trigger reference where relevant.
However:
Dependency Trigger ≠ New Event by default.
If the trigger itself qualifies as an event, upstream TREGA™
governance applies.
Dependency Strength
Dependencies may be qualified by strength.Possible forms may include: essential; material; supporting;
partial; qualified; weak; ambiguous; conflicted.
Strength should reflect governed operational reality.
Strong Dependency ≠ Event Merger.
Essential Dependency
An event may be unable to occur or retain its governed meaningwithout another event.
This may be classified as essential dependency.
Even then:
Essential Dependency ≠ Same Event.
Supporting Dependency
An event may rely on another event without that dependency beingexistential.
ERLDM may preserve supporting dependency where materially
relevant.
Dependency Extent
Dependency may apply to: the whole event; part of the event; oneValue Association; one participant relationship; one operational
component; one execution phase.
Dependency of Part ≠ Dependency of Whole by default.
Dependency Qualification
Dependency may require qualification.Examples include: direct; indirect; partial; conditional;
deferred; provisional; uncertain.
Qualification shall remain explicit.
Qualified Dependency ≠ Defective Dependency.
Dependency Uncertainty
Available information may indicate that dependency exists withoutestablishing its exact form.
ERLDM shall preserve uncertainty.
Dependency Uncertainty ≠ Permission to Assume Independence.
Dependency Conflict
Different systems may describe dependency differently.For example: ERP says Event B depends on Event A; payment system
says Event B depends on Event C; marketplace data suggests both A
and C.
ERLDM shall preserve the conflict.
Dependency Conflict ≠ Permission for Convenient Dependency
Selection.
Dependency Reconsideration
New information may justify reconsidering an earlier Dependencydetermination.
ERLDM shall support reconsideration while preserving prior
history.
Dependency Reconsideration ≠ Historical Erasure.
Dependency Stability
Once dependency is established, it should remain stable unlessmaterially relevant information changes.
Technical migrations or identifier changes should not alter
dependency by themselves.
System Change ≠ Dependency Change by default.
Dependency and Sequence
Dependency and sequence are related but distinct.An event may depend on another event without necessarily
following it in a simple linear time sequence.
Likewise, one event may follow another without depending on it.
Therefore:
Dependency ≠ Sequence.
ERLSM governs sequence.
Dependency and Causation
Dependency may suggest causal relevance.However:
Dependency ≠ Causation by default.
ERLDM does not establish full causal responsibility.
Dependency and Event Formation
ERLDM does not form new events.Dependency Discovery ≠ New Event Formation.
TREFS remains authoritative.
Dependency and Event Boundary
Strong dependency does not remove Event Boundary.Dependency ≠ Shared Event Boundary.
TREBS remains authoritative.
Dependency and Participation
A shared participant may contribute to dependency, but sharedparticipation does not establish dependency by itself.
Shared Participant ≠ Dependency.
TREPS remains authoritative.
Dependency and Value Association
Value relationships may support dependency.However:
Shared Value ≠ Dependency by default.
TRVAS remains authoritative for Value Association.
Dependency and Grouping
Several dependent events may later form an Event Group or EventNetwork.
ERLDM does not establish that grouping.
Dependency Structure ≠ Event Group.
ERLGM governs grouping. Dependency and
Merge / Split
Strong dependency may reveal potential formation or boundaryissues.
It does not authorize merge or split.
Dependency ≠ Merge Criterion by itself.
Dependency ≠ Split Criterion by itself.
ERLMM, together with upstream TREFS and TREBS governance, remains
authoritative.
Dependency and Taxation
Dependency may later be legally relevant for tax analysis.However:
Governed Event Dependency ≠ Tax Dependency Determination.
ERLDM does not determine: taxable supply chains; tax aggregation;
taxable series; Tax Base; tax jurisdiction; Tax Liability;
related-party rules; withholding; deductibility; or another
jurisdiction-specific legal consequence.
Cross-Border Dependency
Events in different jurisdictions may be dependent.For example: order in one country; production in another;
settlement in another; delivery elsewhere.
ERLDM preserves the dependency structure.
It does not determine taxing rights.
Cross-Border Dependency ≠ Tax Jurisdiction.
Blockchain Dependency
Blockchain activity may include dependencies among:smart-contract calls; bridge transactions; settlement
transactions; token transfers; protocol states; off-chain events.
Technical execution dependency may be relevant.
However:
Blockchain Execution Dependency ≠ Tax-Relevant Event Dependency
by default.
The governed Event structure remains decisive.
AI-Agent Dependency
Autonomous agents may create complex dependency graphs.One agent may request activity.
Another may execute it.
A machine may provide resources.
A separate agent may settle value.
ERLDM shall support these relationships.
Agent Coordination ≠ Same Event.
Machine Dependency
Machine-generated events may depend on: prior instructions;system states; resource allocations; sensor conditions; other
machine events.
ERLDM may represent these dependencies without requiring human
involvement.
Machine Dependency ≠ Ungoverned Dependency.
Dependency Traceability
Dependency decisions shall remain reconstructable.Traceability may include: candidate relationship; dependency
indicators; direction; conditions; qualification; extent;
confidence; ambiguity; conflict; correction; and reconsideration.
Dependency Traceability ≠ Event Record Governance.
TREGS remains authoritative for the complete Event Record.
Governance States
ERLDM may represent:Dependency Governance Ready
Dependency Under Governance
No Material Dependency Established
Direct Dependency
Indirect Dependency
Unidirectional Dependency
Mutual Dependency
Conditional Dependency
Partial Dependency
Structural Dependency
Operational Dependency
Value-Related Dependency
Execution Dependency
Settlement Dependency
Dependency Qualified
Dependency Ambiguous
Dependency Conflicted
Dependency Unresolved
Governed Event Dependency Established
Governance Requirements
ERLDM implementations shall ensure that: dependency is governedonly after Event Relationship candidacy is established;
dependency remains distinct from Event Identity; dependency
direction is explicit; unidirectional and mutual dependency can
be represented; conditional dependency can be represented;
partial dependency can be represented; structural and operational
dependency remain distinguishable; value-related dependency does
not replace TRVAS governance; one-to-one, one-to-many,
many-to-one, and many-to-many dependencies can be represented;
direct and indirect dependencies remain distinguishable;
dependency strength and extent can be qualified; dependency
uncertainty remains visible; dependency conflict remains visible;
dependency reconsideration remains traceable; system changes do
not automatically change dependency; dependency remains distinct
from sequence; dependency does not establish causation by
default; Event Formation remains under TREFS; Event Boundary
remains under TREBS; Event Participation remains under TREPS;
Value Association remains under TRVAS; grouping remains under
ERLGM; merge and split remain under ERLMM; and
jurisdiction-specific tax interpretation remains downstream.
Governance Logic
IF ERLIM establishes a valid Relationship Candidate, THEN ERLDMshall evaluate whether a material dependency exists among the
involved events.
IF Event B materially relies on Event A, THEN a dependency may be
established with explicit direction.
IF dependency operates in both directions, THEN mutual dependency
may be represented without merging the events.
IF dependency exists only under a condition, THEN the condition
shall remain explicit.
IF dependency applies only to part of an event, THEN partial
dependency shall be preserved rather than generalized to the
entire event.
IF multiple events contribute to one dependent event, THEN
many-to-one dependency may be represented without merging the
source events.
IF one event creates dependencies for several events, THEN
one-to-many dependency may be represented without creating one
combined event.
IF dependency is uncertain or conflicted, THEN the applicable
governance state shall remain visible.
IF dependency information suggests a potential Event Formation or
Boundary problem, THEN the issue shall be referred to the
appropriate upstream governance layer rather than resolved inside
ERLDM.
IF the dependency structure is sufficiently governed, THEN it
shall proceed to ERLSM for Event Relationship Sequence
governance.
Minimum Implementation Framework
A minimum ERLDM implementation should support:Relationship Candidate Reference The ERLIM candidate under
dependency governance.
Primary Event Reference The first governed event involved.
Dependent Event Reference The event potentially dependent on
another event.
Dependency Identifier A stable identifier for the dependency
relationship.
Dependency Direction The directional structure of dependency.
Dependency Type Direct, indirect, conditional, partial,
structural, operational, value-related, or other governed type.
Dependency Basis The governed information supporting dependency.
Dependency Condition Any condition required for the dependency to
operate.
Dependency Trigger Reference Where a trigger contributes
materially to dependency.
Dependency Extent Whole-event or partial-event dependency.
Dependency Cardinality One-to-one, one-to-many, many-to-one, or
many-to-many.
Dependency Strength The qualified strength of dependency.
Dependency Confidence Confidence in the dependency determination.
Ambiguity State Whether material uncertainty remains.
Conflict State Whether materially conflicting dependency
information exists.
Prior Dependency Reference Where dependency has been reconsidered
or corrected.
Correction / Reconsideration Reference The relevant governance
history.
Traceability Reference Information required to reconstruct the
dependency decision.
Governance State The current ERLDM state.
Handoff State Whether the dependency structure is ready for
ERLSM.
Governance Outputs
ERLDM may produce: Governed Event Dependency; UnidirectionalDependency; Mutual Dependency; Conditional Dependency; Partial
Dependency; Structural Dependency; Operational Dependency;
Value-Related Dependency; Execution Dependency; Fulfillment
Dependency; Settlement Dependency; Refund Dependency; Reversal
Dependency; Replacement Dependency; Continuation Dependency;
Parent–Child Dependency; One-to-One Dependency; One-to-Many
Dependency; Many-to-One Dependency; Many-to-Many Dependency;
Dependency Direction Record; Dependency Condition Record;
Dependency Extent Record; Dependency Strength State; Dependency
Confidence State; Dependency Ambiguity State; Dependency Conflict
State; Dependency Traceability Record; and the principal output:
Governed Event Dependency Structure.
Critical Distinctions
Event Dependency ≠ Event Identity.Relationship Candidate ≠ Dependency by default.
A
↓
B ≠ B
↓
A.
Mutual Dependency ≠ Single Event by default.
Conditional Dependency ≠ Authority Governance.
Partial Dependency ≠ Full Event Dependency.
Structural Dependency ≠ Same Event Structure.
Operational Dependency ≠ Legal Dependency.
Value Dependency ≠ Value Ownership.
Settlement Dependency ≠ Event Merge.
Refund Dependency ≠ Tax Adjustment Determination.
Reversal Dependency ≠ Original Event Erasure.
Continuation Dependency ≠ Same Event Continuity by default.
Parent–Child Dependency ≠ Event Ownership.
One Source Event ≠ One Dependent Event.
Many Dependencies ≠ Event Merge by default.
Indirect Dependency ≠ Irrelevant Dependency.
Immediate Dependency ≠ Temporal Immediacy.
Dependency Condition ≠ Event Identity.
Strong Dependency ≠ Event Merger.
Essential Dependency ≠ Same Event.
Dependency of Part ≠ Dependency of Whole by default.
Qualified Dependency ≠ Defective Dependency.
Dependency Uncertainty ≠ Permission to Assume Independence.
Dependency Conflict ≠ Permission for Convenient Dependency
Selection.
System Change ≠ Dependency Change by default.
Dependency ≠ Sequence.
Dependency ≠ Causation by default.
Dependency Discovery ≠ New Event Formation.
Dependency ≠ Shared Event Boundary.
Shared Participant ≠ Dependency.
Shared Value ≠ Dependency by default.
Dependency Structure ≠ Event Group.
Dependency ≠ Merge Criterion by itself.
Governed Event Dependency ≠ Tax Dependency Determination.
Cross-Border Dependency ≠ Tax Jurisdiction.
Blockchain Execution Dependency ≠ Tax-Relevant Event Dependency
by default.
Agent Coordination ≠ Same Event.
Dependency Traceability ≠ Event Record Governance.
Enterprise Application
ERLDM provides a governed dependency layer for systems in whichone event relies materially on another event but must remain
independently identifiable.
A typical path is:
ERLIM — Governed Event Relationship
Candidate Set
→ ERLDM — Governed Event Dependency Structure→ ERLSM — Event Relationship Sequence
→ ERLGM — Event Relationship Grouping
→ ERLMM — Merge & Split Governance
→ Governed Event Relationship Structure
This enables enterprises, platforms, banks, autonomous systems,
and tax infrastructure to distinguish between events that merely
occur near each other and events that are operationally
dependent. Use Case 1 — Settlement Dependent on Multiple
Commercial Events
A payment platform creates one merchant settlement covering
hundreds of earlier sales events.
The settlement event cannot be understood independently from
those earlier events, but the sales remain separate governed
events.
ERLDM establishes a many-to-one dependency structure between the
sales and the settlement.
The dependency can remain explicit without merging the sales into
one event or treating the settlement as identical to any one
purchase.
The resulting dependency structure can then move to ERLSM for
sequence governance and later to grouping where appropriate. Use
Case 2 — Autonomous Resource Execution Dependency
An AI agent requests additional computational capacity.
A resource-allocation event occurs only after the request is
accepted.
A machine-execution event then depends on that allocation.
Digital settlement depends on measured resource consumption.
ERLDM governs the dependencies among these independently formed
events:
Request
↓
Allocation
↓
Execution
↓
Settlement
It does not determine their final sequence, grouping, tax
treatment, or whether some technical operations belong to the
same event.
The result is a governed dependency structure suitable for
subsequent TRERLS processing.
Canonical Boundary
ERLDM owns the establishment, direction, qualification, extent,cardinality, conditionality, uncertainty, conflict,
reconsideration, continuity, and dependency-specific traceability
of dependencies among Event Relationship Candidates admitted by
ERLIM.
ERLDM does not identify initial Relationship Candidates, govern
Event Sequence, create Event Groups or Event Networks, merge or
split events, form new events, redefine Event Boundaries,
determine Event Timing, Event Location, Event Participation,
Value Association, accountability, liability, tax aggregation,
Tax Base, Tax Liability, or another jurisdiction-specific legal
conclusion.
Its governance ends when material Event Dependencies are
sufficiently represented for downstream Event Relationship
Sequence governance under ERLSM.
Canonical Handoff
ERLIM — Governed Event Relationship Candidate Set↓
ERLDM —
Governed Event Dependency Structure
↓
ERLSM — Event Relationship
Sequence Governance