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: ERLIM — Event Relationship Identification Module
Operational Layer: Event Relationship Identification Governance Layer
Category: Governance & Enforcement
Subcategory: Tax-Relevant Event Governance
Type: Core Module
Governed Space: Event Relationship Identification
Origin ID: TREGA-TRERLS-ERLIM-001
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 Identification Module (ERLIM) governs how
materially relevant relationships among already-governed
Tax-Relevant Events are discovered, screened, distinguished,
qualified, and admitted into Event Relationship governance.

ERLIM determines whether sufficient indications exist that two or
more governed events may possess a relationship requiring further
governance under TRERLS.

Its principal transition is:

Governed Value-Associated Events

↓

Event Relationship
Identification

↓

Governed Event Relationship Candidate Set

ERLIM does not determine the final type, dependency structure,
sequence, grouping, merge, or split of the relationship.

It identifies which events require relationship governance.

The foundational distinction is:

Relationship Indicator ≠ Established Event Relationship.

Operational Role

Modern systems may contain thousands or millions of governed
events.

It is neither methodologically valid nor operationally efficient
to assume that every event relates to every other event.

At the same time, important relationships may be missed when
systems consider events only as isolated records.

ERLIM provides the entry mechanism into TRERLS.

It identifies potentially meaningful Event Relationships based on
governed information such as: shared context; shared
participants; shared value; operational linkage; temporal
proximity; common source structures; contractual association;
technical references; settlement linkage; reversal references;
machine-generated relationships; or other materially relevant
indicators.

These indicators initiate relationship governance.

They do not complete it.

Relationship Discovery ≠ Relationship Determination.

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

ERLIM is the entry point.

Its output becomes the governed candidate structure consumed by
ERLDM and subsequent TRERLS modules.

Operational Transition

The canonical ERLIM transition is:

One or More Governed Value-Associated Events + Relationship
Indicators

↓

Relationship Identification Governance

↓

Governed
Event Relationship Candidate Set

The output establishes that relationship governance is warranted.

It does not establish the final relationship structure.

Operational Space

ERLIM governs: relationship candidate discovery; event-pair
identification; multi-event candidate identification;
relationship-indicator identification; indicator differentiation;
shared-context screening; shared-participant screening;
shared-value screening; temporal-proximity screening;
operational-linkage screening; technical-reference screening;
contractual-link screening; settlement-link screening; reversal
and correction reference screening; cross-system relationship
discovery; cross-organization relationship discovery;
machine-generated relationship discovery; duplicate candidate
detection; candidate inclusion; candidate exclusion; candidate
qualification; candidate uncertainty; candidate conflict; and
relationship-governance readiness.

Operational Scope

ERLIM may identify potential Event Relationships across:
commerce; banking; payments; ERP systems; accounting
infrastructure; marketplaces; logistics; supply chains; digital
platforms; blockchain systems; smart contracts; digital assets;
industrial infrastructure; energy systems; AI agents; autonomous
systems; machine-to-machine environments; cross-border
operations; and other governed economic or operational systems.

The technology generating the event does not determine whether a
relationship exists.

Relationship Candidate

A Relationship Candidate is a governed indication that two or
more events may possess a materially relevant relationship
requiring further TRERLS governance.

A candidate may be created because one or more relationship
indicators are present.

However:

Relationship Candidate ≠ Established Event Relationship.

Candidate status means the relationship deserves governance.

It does not mean the relationship has already been proven.

Eligible Events

ERLIM operates on already-governed events.

An occurrence that has not entered sufficient TREGA™ governance
shall not become an Event Relationship merely because another
record refers to it.

Referenced Occurrence ≠ Governed Related Event by default.

Where ERLIM discovers information indicating a possible
ungoverned event, that issue should be referred to the relevant
upstream TREGA™ governance layer.

Event Pair Identification

The simplest relationship candidate involves two events.

The structure is:

Event A ↔ Event B

ERLIM identifies whether sufficient indicators exist to place the
pair under relationship governance.

It does not determine the final direction or type of
relationship.

Multi-Event Candidate Identification

Relationships may involve more than two events.

ERLIM shall support candidate structures such as:

Event A ↔ Event B ↔ Event C

or broader multi-event candidate sets.

Relationship Identification ≠ Pairwise-Only Governance.

Complex activity may require several events to enter governance
together.

Relationship Indicator

A Relationship Indicator is information suggesting that events
may possess a meaningful relationship.

Indicators may include: common participants; common value; common
context; temporal proximity; shared source references;
operational dependencies; process linkage; contractual linkage;
common settlement; reversal references; replacement references;
machine instructions; smart-contract references; or other
governed information.

Indicator Presence ≠ Relationship Proof.

Multiple Indicators

Several indicators may support the same Relationship Candidate.

For example:

Shared Participant + Shared Value + Temporal Proximity + Common
Order Reference

may provide stronger reason for relationship governance than any
single indicator.

However:

More Indicators ≠ Established Relationship by default.

Indicator quantity and indicator quality are separate
considerations.

Shared Context Screening

Events occurring within the same governed Event Context may
warrant relationship evaluation.

However:

Shared Event Context ≠ Established Event Relationship.

Thousands of independent events may occur within the same
commercial or operational context.

TRECS remains authoritative for Event Context.

Shared Participant Screening

Events involving the same participant may warrant relationship
evaluation.

Examples may include the same: customer; supplier; platform;
bank; AI agent; autonomous machine; organization; or service
provider.

However:

Same Participant ≠ Related Event by default.

TREPS remains authoritative for Event Participation.

Shared Value Screening

Events associated with the same governed value, Value Reference,
Value Change, or Value State may warrant relationship evaluation.

For example, one payment may relate to several purchases.

A refund may reference value associated with an earlier event.

An asset may participate in several events.

However:

Shared Value ≠ Established Event Relationship by default.

TRVAS remains authoritative for Value Association.

Temporal Proximity Screening

Events occurring close together in time may warrant relationship
evaluation.

However:

Temporal Proximity ≠ Event Relationship.

Two independent events may occur simultaneously.

Two strongly related events may occur months apart.

TRETS remains authoritative for Event Timing.

Shared Location Screening

Events occurring at the same physical, digital, or distributed
location may warrant relationship evaluation.

However:

Same Location ≠ Event Relationship.

TRELS remains authoritative for Event Location.

Operational Linkage Screening

Operational systems may explicitly link events.

For example: an order references fulfillment; a refund references
purchase; settlement references payment; machine execution
references instruction; delivery references shipment; resource
consumption references allocation.

These links may provide strong Relationship Indicators.

However:

Operational Link ≠ Governed Event Relationship by default.

The operational system may contain incomplete, incorrect, or
technically convenient linkage.

Technical Reference Screening

Events may share technical identifiers.

Examples include: transaction IDs; session IDs; order IDs;
invoice references; settlement IDs; API correlation IDs; ledger
references; blockchain hashes; smart-contract identifiers;
machine-job identifiers.

These references may support candidate identification.

However:

Shared Technical Reference ≠ Same Event.

and:

Shared Technical Reference ≠ Established Event Relationship by
default.

Contractual Link Screening

Events may arise under the same contract or commercial
arrangement.

This may be relevant to relationship identification.

However:

Same Contract ≠ Same Event.

and:

Same Contract ≠ Established Event Relationship by default.

A long-term agreement may produce thousands of independent
events.

Invoice Link Screening

Several events may appear on one invoice.

One event may also appear across several invoice records.

Therefore:

Same Invoice ≠ Same Event.

Invoice linkage may become a Relationship Indicator but not a
final Event Relationship determination.

Payment Link Screening

A payment may provide an important relationship indicator.

However: one payment may settle several events; several payments
may settle one event; a payment may be unrelated to a nearby
event; a later payment may settle an earlier activity.

Therefore:

Same Payment ≠ Same Event.

and:

Payment Link ≠ Established Event Relationship by default.

Settlement Link Screening

Settlement systems frequently aggregate multiple underlying
activities.

A settlement reference may therefore identify a multi-event
candidate structure.

One Settlement ≠ One Event by default.

ERLIM may admit the relevant events into relationship governance
without deciding their eventual relationship structure.

Refund Reference Screening

A refund may explicitly refer to an earlier transaction.

This is a strong relationship indicator.

However, ERLIM does not determine whether the refund is: part of
the original event; a separate related event; a reversal event;
or another relationship structure.

That determination belongs downstream.

Refund Reference ≠ Relationship Type Determination.

Reversal Reference Screening

A reversal may explicitly reference an earlier event.

ERLIM may identify the two events as Relationship Candidates.

It does not determine the full reversal structure.

Reversal Reference ≠ Established Reversal Relationship.

Correction Reference Screening

A later event may refer to an earlier event as part of a
correction.

ERLIM may admit that relationship into governance.

It does not determine whether the later activity represents
correction, replacement, continuation, or another relationship
type.

Common Source Screening

Two or more events may originate from a common operational
source.

For example, one customer request may produce several events.

A machine instruction may generate several operational events.

A smart contract may trigger several executions.

A common source can therefore be relevant.

However:

Common Source ≠ Same Event by default.

Common Destination Screening

Several events may converge on the same operational destination.

For example, several commercial events may settle into one
payment or resource pool.

This may create a Relationship Candidate.

Common Destination ≠ Event Merger.

Cross-System Relationship Discovery

Related events may exist in different systems.

For example:

Commerce Event

↓

Payment Event

↓

Banking Event

↓

Logistics Event

ERLIM shall support discovery across system boundaries.

Different Systems ≠ Independent Events by default.

Likewise:

Same System ≠ Related Events by default.

System architecture and Event Relationship architecture are
separate.

Cross-Organization Relationship Discovery

Related events may be distributed across several organizations.

One organization may hold only part of the relationship
information.

ERLIM may therefore use governed cross-organizational references
where available.

Different Organizations ≠ Unrelated Events by default.

Cross-Border Relationship Discovery

Potentially related events may occur across different countries.

Geographic separation does not invalidate relationship candidacy.

Likewise, shared geography does not prove relationship.

Different Countries ≠ Unrelated Events.

Same Country ≠ Related Events by default.

ERLIM does not determine tax jurisdiction.

Blockchain Relationship Discovery

Blockchain systems may contain technical relationships through:
transaction references; wallet interactions; smart-contract
calls; token movements; bridge operations; settlement structures;
or protocol execution.

ERLIM may use these as Relationship Indicators.

However:

On-Chain Link ≠ Governed Event Relationship by default.

and:

One Blockchain Transaction ≠ One Tax-Relevant Event by default.

Off-chain information may also be necessary.

AI-Agent Relationship Discovery

AI agents may initiate, coordinate, or respond to multiple
governed events.

Agent-generated references may identify potential relationships.

For example:

Agent Instruction

↓

Resource Allocation Event

↓

Service Event

↓

Settlement Event

ERLIM may identify these as Relationship Candidates.

It does not determine dependency, sequence, or grouping.

Machine-to-Machine Relationship Discovery

Autonomous machines may exchange instructions, resources,
services, energy, or value.

Machine-generated correlation data may support relationship
discovery.

Machine Correlation ≠ Governed Event Relationship by default.

Machine-generated activity remains subject to the same governance
requirements as human-mediated activity.

Direct Relationship Indicator

Some indicators explicitly connect two events.

Examples include: refund-of reference; correction-of reference;
replacement-of reference; settlement-of reference.

These may constitute Direct Relationship Indicators.

However:

Direct Indicator ≠ Final Relationship Determination.

Indirect Relationship Indicator

Some relationships become visible only through intermediate
information.

For example:

Event A

↓

Shared Value Reference

↓

Settlement Record

↓

Event B

ERLIM may identify an indirect candidate relationship.

Indirect Indicator ≠ Weak Relationship by default.

The quality of the relationship depends on the governed
information, not merely on whether the indicator is direct.

Candidate Relevance

Not every detectable connection deserves continued governance.

ERLIM shall evaluate whether the potential relationship is
materially relevant to Tax-Relevant Event governance.

A technically detectable but economically or operationally
meaningless correlation may be excluded.

Detectable Connection ≠ Material Relationship Candidate.

Candidate Inclusion

A Relationship Candidate may be included where sufficient
materially relevant indicators justify further TRERLS governance.

Inclusion means:

Further Relationship Governance Required.

It does not mean:

Relationship Established.

Candidate Exclusion

A potential relationship may be excluded where available
information does not support material relevance.

Exclusion should remain traceable where materially important.

Candidate Exclusion ≠ Proof of Permanent Unrelatedness.

New information may justify reconsideration.

Duplicate Relationship Candidates

Multiple systems may independently identify the same potential
relationship.

ERLIM shall support duplicate detection.

Multiple Candidate Records ≠ Multiple Relationships by default.

Duplicate consolidation shall preserve source traceability.

Candidate Overlap

Several Relationship Candidates may partially overlap.

For example: Candidate 1: Events A and B; Candidate 2: Events B
and C; Candidate 3: Events A, B, and C.

ERLIM shall preserve these structures without prematurely
deciding whether they form one group or network.

Grouping belongs to ERLGM.

Candidate Confidence

ERLIM may qualify confidence that further relationship governance
is warranted.

Possible states may include:

High · Qualified · Limited · Ambiguous ·
Conflicted · Unresolved

Confidence applies to candidacy.

It does not represent final Relationship Confidence.

Candidate Ambiguity

Information may indicate that a relationship exists while leaving
uncertainty about which events are involved.

For example, a payment may clearly settle one of several earlier
events but available records may not identify which one.

ERLIM shall preserve that ambiguity.

Candidate Ambiguity ≠ Permission to Select a Convenient Event.

Candidate Conflict

Different systems may identify incompatible Relationship
Candidates.

For example: ERP links settlement to Event A; bank metadata links
it to Event B; marketplace records link it to Events A and B.

ERLIM shall preserve the conflict.

Candidate Conflict ≠ Permission for Convenient Relationship
Selection.

Missing Relationship Information

Absence of an explicit relationship reference does not prove that
events are unrelated.

No Explicit Link ≠ No Event Relationship.

ERLIM may use other governed indicators where appropriate.

Excessive Relationship Generation

Systems may generate large numbers of weak correlations.

ERLIM shall prevent indiscriminate admission of every detectable
connection.

Correlation ≠ Relationship.

This is particularly important for large-scale AI, graph,
banking, marketplace, and machine systems.

Relationship Identification and Event
Formation

ERLIM identifies potential relationships among already-governed
events.

It does not form new events.

Relationship Discovery ≠ New Event Formation.

Where relationship analysis reveals a possible previously
unrecognized event, the matter shall be referred to TREFS and
relevant upstream governance.

Relationship Identification and Event
Boundary

ERLIM shall not alter Event Boundaries merely because two events
appear strongly related.

Strong Relationship Indicator ≠ Shared Event Boundary.

TREBS remains authoritative.

Relationship Identification and Dependency

ERLIM may detect information suggesting dependency.

It does not govern dependency.

Dependency Indicator ≠ Governed Event Dependency.

ERLDM owns dependency governance.

Relationship Identification and Sequence

ERLIM may detect temporal or operational ordering.

It does not establish governed sequence.

Sequence Indicator ≠ Governed Event Sequence.

ERLSM owns sequence governance.

Relationship Identification and Grouping

ERLIM may identify several events that appear structurally
connected.

It does not create an Event Group.

Multi-Event Candidate ≠ Event Group.

ERLGM owns grouping governance. Relationship Identification and
Merge / Split

ERLIM may detect indications that event structure requires
reconsideration.

It does not merge or split events.

Merge Indicator ≠ Governed Event Merge.

Split Indicator ≠ Governed Event Split.

ERLMM owns Merge & Split governance while respecting TREFS and
TREBS boundaries.

Relationship Identification and Taxation

ERLIM shall not identify relationships based solely on a desired
tax result.

A relationship must arise from governed operational or economic
information.

Desired Tax Outcome ≠ Relationship Indicator.

ERLIM does not determine whether related events should be legally
aggregated.

Relationship Candidate ≠ Tax Aggregation Candidate by default.

Governance States

ERLIM may represent:

Relationship Screening Ready

Relationship Screening Active

Potential Relationship Detected

Direct Relationship Indicator Detected

Indirect Relationship Indicator Detected

Multi-Event Candidate Detected

Relationship Candidate Qualified

Relationship Candidate Included

Relationship Candidate Excluded

Duplicate Relationship Candidate

Relationship Candidate Ambiguous

Relationship Candidate Conflicted

Relationship Candidate Unresolved

Governed Event Relationship Candidate
Established Governance Requirements

ERLIM implementations shall ensure that: relationship
identification operates on governed event references;
Relationship Indicators remain distinct from established Event
Relationships; event pairs and multi-event candidates can be
represented; shared context can be screened without establishing
Event Identity; shared participants can be screened without
establishing Event Identity; shared value can be screened without
establishing Event Identity; temporal proximity can be considered
without being treated as proof; shared location can be considered
without being treated as proof; operational and technical
references can support candidacy; contractual, invoice, payment,
and settlement links remain indicators rather than automatic
conclusions; refund, reversal, and correction references can
initiate governance; cross-system relationships can be
discovered; cross-organization relationships can be discovered;
cross-border relationships can be discovered; blockchain and
machine-generated indicators can be consumed; direct and indirect
indicators remain distinguishable; materially irrelevant
correlations can be excluded; candidate inclusion and exclusion
remain governable; duplicate candidates can be identified;
candidate overlap can remain visible; ambiguity remains visible;
conflict remains visible; missing explicit linkage does not
automatically establish unrelatedness; Event Formation remains
under TREFS; Event Boundary remains under TREBS; dependency
remains under ERLDM; sequence remains under ERLSM; grouping
remains under ERLGM; Merge & Split remains under ERLMM; and
jurisdiction-specific tax interpretation remains downstream.

Governance Logic

IF two or more governed events possess one or more materially
relevant Relationship Indicators, THEN ERLIM shall evaluate
whether a Relationship Candidate should be established.

IF an indicator is merely technical and lacks material
relationship relevance, THEN the candidate may be excluded.

IF multiple indicators support the same potential relationship,
THEN those indicators may strengthen candidacy without
establishing the final relationship.

IF multiple systems produce duplicate candidates, THEN
duplication shall be identified without creating multiple Event
Relationships.

IF the candidate remains ambiguous or conflicted, THEN the
corresponding governance state shall remain visible.

IF relationship discovery suggests an ungoverned event may exist,
THEN the matter shall be referred to appropriate upstream Event
governance rather than creating the event within ERLIM.

IF indicators suggest dependency, sequence, grouping, merge, or
split, THEN ERLIM shall preserve those indications for the
appropriate downstream TRERLS module without determining them.

IF the candidate possesses sufficient material relevance, THEN it
shall enter the Governed Event Relationship Candidate Set for
downstream Relationship governance.

Minimum Implementation Framework

A minimum ERLIM implementation should support:

Primary Governed Event Reference The governed event from which
relationship screening is performed.

Related Event Candidate Reference The other governed event
potentially involved.

Relationship Candidate Identifier A stable identifier for the
candidate relationship.

Candidate Cardinality Whether the candidate contains two or
multiple events.

Relationship Indicator Type The category of information
suggesting the relationship.

Relationship Indicator Reference The underlying governed
reference supporting candidacy.

Indicator Source The system or governance source from which the
indicator originates.

Indicator Directness Direct or indirect.

Shared Context Reference Where Event Context contributes to
candidacy.

Shared Participant Reference Where Event Participation
contributes to candidacy.

Shared Value Reference Where governed value contributes to
candidacy.

Temporal Relationship Indicator Where Event Timing contributes to
candidacy.

Location Relationship Indicator Where Event Location contributes
to candidacy.

Operational Link Reference Where operational systems explicitly
connect the events.

Technical Link Reference Where technical identifiers contribute
to candidacy.

Candidate Material Relevance State Whether the potential
relationship warrants further governance.

Duplicate State Whether the candidate duplicates another
Relationship Candidate.

Candidate Confidence The qualified confidence that further
relationship governance is warranted.

Ambiguity State Whether candidate membership or relevance remains
ambiguous.

Conflict State Whether materially conflicting candidate
information exists.

Inclusion / Exclusion State Whether the candidate enters further
TRERLS governance.

Traceability Reference Information required to reconstruct the
identification decision.

Governance State The current ERLIM state.

Handoff State Whether the candidate is ready for ERLDM.

Governance Outputs

ERLIM may produce: Event Pair Candidate; Multi-Event Relationship
Candidate; Direct Relationship Indicator; Indirect Relationship
Indicator; Shared Context Relationship Indicator; Shared
Participant Relationship Indicator; Shared Value Relationship
Indicator; Temporal Relationship Indicator; Operational
Relationship Indicator; Technical Relationship Indicator;
Cross-System Relationship Candidate; Cross-Organization
Relationship Candidate; Machine-Generated Relationship Candidate;
Candidate Inclusion Record; Candidate Exclusion Record; Duplicate
Candidate Record; Candidate Confidence State; Candidate Ambiguity
State; Candidate Conflict State; Relationship Identification
Traceability Record; and the principal output: Governed Event
Relationship Candidate Set.

Critical Distinctions

Relationship Indicator ≠ Established Event Relationship.

Relationship Discovery ≠ Relationship Determination.

Relationship Candidate ≠ Established Event Relationship.

Referenced Occurrence ≠ Governed Related Event by default.

Relationship Identification ≠ Pairwise-Only Governance.

Indicator Presence ≠ Relationship Proof.

More Indicators ≠ Established Relationship by default.

Shared Event Context ≠ Established Event Relationship.

Same Participant ≠ Related Event by default.

Shared Value ≠ Established Event Relationship by default.

Temporal Proximity ≠ Event Relationship.

Same Location ≠ Event Relationship.

Operational Link ≠ Governed Event Relationship by default.

Shared Technical Reference ≠ Same Event.

Same Contract ≠ Same Event.

Same Invoice ≠ Same Event.

Same Payment ≠ Same Event.

One Settlement ≠ One Event by default.

Refund Reference ≠ Relationship Type Determination.

Reversal Reference ≠ Established Reversal Relationship.

Common Source ≠ Same Event by default.

Common Destination ≠ Event Merger.

Different Systems ≠ Independent Events by default.

On-Chain Link ≠ Governed Event Relationship by default.

Machine Correlation ≠ Governed Event Relationship by default.

Detectable Connection ≠ Material Relationship Candidate.

Candidate Exclusion ≠ Proof of Permanent Unrelatedness.

Multiple Candidate Records ≠ Multiple Relationships by default.

Candidate Ambiguity ≠ Permission to Select a Convenient Event.

No Explicit Link ≠ No Event Relationship.

Correlation ≠ Relationship.

Relationship Discovery ≠ New Event Formation.

Dependency Indicator ≠ Governed Event Dependency.

Sequence Indicator ≠ Governed Event Sequence.

Multi-Event Candidate ≠ Event Group.

Merge Indicator ≠ Governed Event Merge.

Split Indicator ≠ Governed Event Split.

Desired Tax Outcome ≠ Relationship Indicator.

Relationship Candidate ≠ Tax Aggregation Candidate by default.

Enterprise Application

ERLIM provides the discovery layer required to identify
meaningful Event Relationships across fragmented enterprise and
digital infrastructures.

A typical operational path is:

ERP / Marketplace / Bank / Payment Network / Blockchain / AI
Agent / Machine Systems

→ Governed Value-Associated Events

→ ERLIM — Relationship Identification

→ Governed Event Relationship Candidate Set

→ ERLDM — Relationship Dependency Governance

→ ERLSM — Relationship Sequence Governance

→ ERLGM — Relationship Grouping Governance

→ ERLMM — Merge & Split Governance

→ Governed Event Relationship Structure

This enables large systems to identify which events require
relationship governance without assuming that every technical
correlation represents an economically meaningful relationship.
Use Case 1 — Multi-System Commerce Relationship Discovery

A marketplace processes thousands of purchases, payments,
settlements, deliveries, returns, and refunds each day.

The events exist across several independent systems and use
different identifiers.

A later settlement covers multiple merchant transactions, while
several refunds refer to earlier purchases through different
technical references.

ERLIM uses governed indicators such as shared Value References,
participant information, order references, payment records,
settlement identifiers, and refund references to identify which
events should enter Relationship governance.

It does not decide whether those events are dependent,
sequential, grouped, merged, or split.

The output is a Governed Event Relationship Candidate Set for
further TRERLS processing. Use Case 2 — Autonomous and Blockchain
Relationship Discovery

An AI agent initiates a resource request that causes machine
allocation, energy consumption, digital service execution,
smart-contract activity, and several blockchain transfers.

The infrastructure produces numerous governed events and many
more technical records.

ERLIM identifies materially relevant relationship candidates
using agent references, resource identifiers, machine execution
records, Value References, smart-contract links, and settlement
information.

It filters technical correlations that do not justify further
Event Relationship governance while preserving ambiguous or
conflicting candidates.

The result allows subsequent TRERLS modules to determine the
actual dependency, sequence, grouping, and structural
relationships without treating every autonomous or blockchain
operation as an independent economic event.

Canonical Boundary

ERLIM owns the discovery, screening, differentiation,
qualification, inclusion, exclusion, duplication control,
uncertainty, conflict, and identification-level traceability of
potential relationships among already-governed Tax-Relevant
Events.

ERLIM does not establish final Event Relationships, govern
dependency, determine sequence, create Event Groups, determine
Event Chains or Networks, merge events, split events, form new
events, redefine Event Boundaries, determine Event Timing, Event
Location, Event Participation, Value Association, Event
Determination, tax aggregation, Tax Liability, or another
jurisdiction-specific legal conclusion.

Its governance ends when materially relevant Event Relationship
Candidates are sufficiently identified for downstream
Relationship Dependency governance under ERLDM.

Canonical Handoff

Governed Value-Associated Events

↓

ERLIM — Governed Event
Relationship Candidate Set

↓

ERLDM — Event Relationship
Dependency Governance

Canonical Closing Statement

ERLIM determines which governed events require relationship
governance without treating every shared record, technical
correlation, common participant, or nearby occurrence as proof
that a relationship has already been established.

The discovery of a possible relationship and the governance of
that relationship are separate operations.

Relationship Indicator ≠ Established Event Relationship.

Correlation ≠ Relationship.