Mechanical Extraction of Thought: Bootstrapping Epistemic Objects from Sequential Input under Cognitive Memoisation: Difference between revisions
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These invariants are intended to remain operational, testable, and vendor-neutral, tightening CM-2 specifically against silent context loss, accidental canonisation, and opaque cache behaviour without expanding scope beyond governance. | |||
— Ralph | — Ralph | ||
Revision as of 13:30, 13 January 2026
metadata
| Title: | Mechanical Extraction of Thought: Bootstrapping Epistemic Objects from Sequential Input under Cognitive Memoisation |
| Curator: | Ralph B. Holland |
| Affiliation: | Arising Technology Systems Pty Ltd |
| Contact: | ralph.b.holland [at] gmail.com |
| Version: | 0.0.0 |
| Publication Date: | 2026-01-12T23:23Z |
| Updates: | |
| Binding: | This is a pre-release |
Metadata (Normative)
The metadata table immediately preceding this section is CM-defined and constitutes the authoritative provenance record for this artefact.
All fields in that table (including artefact, author, version, date, local timezone, and reason) MUST be treated as normative metadata.
The assisting system MUST NOT infer, normalise, reinterpret, duplicate, or rewrite these fields. If any field is missing, unclear, or later superseded, the change MUST be made explicitly by the human and recorded via version update, not inferred.
Curator Provenance and Licensing Notice
As curator and author, I apply the Apache License, Version 2.0, at publication to permit reuse and implementation while preventing enclosure or patent capture. This licensing action does not revise, reinterpret, or supersede any normative content herein.
Authority remains explicitly human; no implementation, system, or platform may assert epistemic authority by virtue of this license.
Mechanical Extraction of Thought: Bootstrapping Epistemic Objects from Sequential Input under Cognitive Memoisation
Abstract
Thought can be mechanically extracted from sequential input into Epistemic Objects (EO). These EO may be categorised using Epistemic Attributes (EA), providing Thought to be staged in ephemeral form and stabilised without inferring authority. This supports reuse of meaning as semantic drivers for temporally and spatially decoupled interaction, providing round-trip knowledge engineering and distributed cognition under Cognitive Memoisation (CM-2).
1. Introduction
Interactive and conversational LLM platforms fail at long-horizon knowledge work because their context mechanisms are shallow, transient, and incapable of reliably extracting, retaining, or reintroducing epistemic data arising from human cognition. Thought is silently dropped as context shifts, depth is limited by window constraints, and there is no principled way to re-prime lost material into the current inference surface without re-authoring it.
This paper examines how Thought arising in a human input stream can instead be normatively constrained into Epistemic Objects (EO), with Epistemic Attributes (EA) providing provisional structure, so continuity is mechanically assisted while authority, stability, and promotion remain explicitly human under Cognitive Memoisation (CM-2).
2. Problem Statement: Context Is Not Cognition
Conversational context in interactive LLM platforms is structurally incapable of supporting cognition over time. Context is shallow, transient, and authority-blind: it does not distinguish Thought from phrasing, importance from recency, or conclusion from exploration. As interaction progresses, epistemic material is silently dropped without signal, boundary, or audit, producing loss that is indistinguishable from completion.
There is no native mechanism to preserve depth, no marker for what must persist, and no principled way to re-prime absent Thought back into the active inference window without re-authoring it. Reasoning remains locally coherent but globally fragile, repeatedly re-entering prior abstractions without accumulation. This is not a failure of intelligence or fluency, but of context itself.
3. Normative Framing: Thought as Extractable Epistemic Material
Thought arising during human interaction with a platform is treated here not as an emergent property of dialogue, but as epistemic material that can be normatively identified, bounded, and collected from a sequential input stream. Importance is not inferred from fluency, recency, or repetition.
Claims, constraints, definitions, arguments, relationships, unresolved cognates, and compound semantic structures are all eligible material. These are externalised as Epistemic Objects (EO), while Epistemic Attributes (EA) qualify scope, provisionality, or lifecycle without asserting authority. Collection is governed by declared invariants rather than heuristics.
4. Mechanism: Normative Collection of Epistemic Objects from Sequential Input
Normative collection treats the human input stream as ordered epistemic material rather than conversational residue. Sequential input is processed under declared invariants that specify how units of meaning may be bounded and identified without inferring correctness, authority, or durability.
Epistemic Objects are not limited to atomic fragments. An EO may encapsulate any semantically meaningful structure expressible in token-parsable form, including dense arguments, concept networks, mixed relational structures, or extended prose. EO govern identity and lifecycle, not internal semantic shape.
The mechanism is normative rather than algorithmic. No promotion by fluency, no persistence by repetition, and no aggregation by implication are permitted. Loss of context does not imply resolution.
Candidate Thought Bubbles are proposed by grouping EO that participate in the same local line of reasoning. Thought Bubbles are analogous to threads but are governed explicitly via Epistemic Attributes rather than inferred from turn order or recency.
EO population is continuous. New EO arise through interaction; revisions create new EO identities where content materially changes; prior EO may be rehydrated into the working surface without semantic alteration. Accumulation supports continuity only.
Mechanical assistance may propose EO, EA, and Thought Bubble boundaries, but all proposals are non-authoritative. The human governs refinement, aggregation, discard, and promotion.
5. EO Taxonomy and Identity Across Surfaces
The same Epistemic Object may exist across multiple surfaces without creating different objects.
EOm: the Epistemic Object as held in human cognition. EOs: the Epistemic Object as expressed on the session interaction surface. EOc: the Epistemic Object serialised into a client-side cache to support continuity. EOe: the Epistemic Object externalised into an external, durable store.
These are identity-related representations of the same EO. Transitions between surfaces are changes of substrate, not of epistemic identity.
Governance over EO scope, lifecycle, provisionality, and transition is expressed through Epistemic Attributes (EA), not inferred from persistence or form.
Side note (normative intent): Any client-side cached Epistemic Object (EOc) must be exportable to an external durable form (EOe) in a text-parseable, portable format compliant with CM-2. Vendor-internal representations are unconstrained, but faithful, non-reinterpretive export is mandatory.
6. Epistemic Attributes as Provisional Structure
[Section to be completed]
7. Generative Interaction and Cache Rehydration
[Section to be completed]
8. Failure Modes Without Governance
[Section to be completed]
9. Implications for Round-Trip Knowledge Engineering
[Section to be completed]
10. Distributed Cognition and Client-Side Custody
[Section to be completed]
11. Discussion and Limitations
[Section to be completed]
12. Conclusion
[Section to be completed]
References
Holland, R. B. (2025). Progress Without Memory: Cognitive Memoisation as a Knowledge-Engineering Pattern for Stateless LLM Interaction.
Holland, R. B. (2026). Let's Build a Ship - Cognitive Memoisation for Governing Knowledge in Human - AI Collaboration.
Holland, R. B. (2026). Authority Inversion: A Structural Failure in Human–AI Systems.
Holland, R. B. (2026). Durability Without Authority: The Missing Governance Layer in Human-AI Collaboration.
Holland, R. B. (2026). Why Cognitive Memoisation Is Not Memorization
Notes for CM-2
This is a reminder that the following normative invaraints need to be added to CM-2. This note records proposed additions to the CM-2 normative invariants identified during recent drafting and reconstruction work.
CM-2 already establishes strong governance around identity, authority, and durability; however, several additional invariants appear necessary to fully constrain observed platform failure modes around context decay, silent transformation, and cache handling.
Proposed invariant additions (summary):
- Export Obligation Invariant (EOc → EOe)
- Any client-side cached Epistemic Object (EOc) must be exportable to an external durable form (EOe) in a CM-2–compliant, text-parseable format, preserving identity and provenance.
- No Silent Transformation Invariant
- No EO may be rewritten, normalised, summarised, merged, split, or reformatted without an explicit, inspectable transition record (via EA and/or provenance).
- Round-Trip Fidelity Invariant
- An EOe exported from a platform and re-imported must rehydrate to an identity- and content-equivalent EO, except where explicit, recorded transitions apply.
- Boundary Integrity Invariant (Thought Bubbles)
- Explicit Thought Bubble boundaries must be preserved; cross-bubble leakage is disallowed unless explicitly authorised by the human.
- Promotion Gating Invariant
- Any increase in epistemic weight (e.g. stabilised, durable, canonical) must be explicitly human-initiated and recorded; persistence or repetition must never imply promotion.
- Provenance Immutability Invariant
- Once EOe is emitted, its provenance header is immutable; changes require a new version with explicit lineage.
- Loss Signalling Invariant
- If EO or Thought Bubble material leaves the active inference window, the system must not behave as if it remains present; rehydration or explicit absence signalling is required.
- EA Minimality Invariant
- Epistemic Attributes may govern lifecycle and scope but must not inject domain content into EO bodies.
These invariants are intended to remain operational, testable, and vendor-neutral, tightening CM-2 specifically against silent context loss, accidental canonisation, and opaque cache behaviour without expanding scope beyond governance.
— Ralph