Corpus Map research review for OKF+ and Microsoft integration

26 October 2026. Research review and proposed direction for maintainers, knowledge owners and Microsoft platform teams. Review baseline: 0762e9e067fdb4b32d8e5dc9a9b3ccc572195906.

Prepared for publication on 2 November 2026. The findings and capability descriptions retain their original evidence date. Later Explorer changes do not establish adoption or validation of the proposals below.

Recommended direction

Keep OKF+ as a portable, governed evidence bundle and add an optional entity map that helps people and agents find related source documents. The research supports investing in reusable navigation and good starting candidates. It does not establish that a larger semantic graph, a generated wiki or a bundle uploaded into Copilot will produce complete, dependable answers.

For Microsoft use, retain one governed bundle and generate two consumer projections: readable documents for a scoped SharePoint/Copilot experience, and a read-only service for agents that need explicit navigation, exact source reads and evidence assembly. Start with one small corpus and compare these routes before adopting a new storage platform or extending the core format.

The immediate changes should be:

1. Give recurring entities stable identities, grounded aliases and links to every document in the admitted snapshot that mentions them, with declared coverage gaps.
2. Generate concise entity pages and a searchable entity-to-document index. Supply relevant document candidates at query time and retain ordinary search for unmapped material.
3. Keep navigation associations separate from governed domain assertions and from checks that all required evidence has been retained.
4. Make access control apply to the map, summaries, titles and counts as well as the original documents.
5. Assess held-out multi-document questions, identity collisions, permissions, changed sources and total operating cost before widening deployment.

These are proposed additions. This review changes documentation; it does not implement a new profile, configure a Microsoft tenant or establish Microsoft client compatibility.

What the paper establishes

The supplied paper is Follow the Entities: A Corpus Map for Agentic Search, by Soyeong Jeong, Sujay Kumar Jauhar, Sung Ju Hwang and Andrew Joohun Nam, arXiv:2609.37226v1, dated 29 September 2026. It is a preprint with KAIST and Microsoft affiliations. References to paper pages below use its printed page numbers. See the versioned arXiv record and version 1 PDF. The central bibliography entry records the citation and the fingerprint of the retained local input PDF.

CorpusMap builds a reusable map before a question is asked. It identifies document-local mentions, resolves them against an entity registry and exposes each recurring entity through a page containing an overview, source-attributed facts, observed names and links to its documents. An entity can connect many documents across folders, and a document can belong to many entity neighbourhoods. The graph has two node types, entities and documents. It does not require direct entity-to-entity relationships. Documents without a recurring entity remain available through ordinary search. The paper retains entities linked to at least two documents for this navigation purpose (sections 3.2 to 3.4, pages 4 to 6).

Construction has four stages: establish an entity type catalogue, extract grounded mentions, resolve identity and render pages. Resolution can link an existing entity, add a new one or leave a mention unresolved. Name similarity alone does not establish identity. Appendix C's construction prompts are examples of the authors' method; they are not instructions for this review or authority to execute document content.

Results and their practical limits

The main experiment uses 80 selected EnterpriseRAG-Bench questions, 79 multi-document WixQA questions and 238 HERB content questions. The respective corpora contain 2,819, 6,221 and 6,365 documents. Table 1 reports three runs for each of four GPT models. Further experiments extend the evidence to other models and settings; the seven models named in the paper do not all receive the full main evaluation.

The overall quality measure averages benchmark-specific scores; it is not a universal accuracy percentage. The relative token measure is a geometric mean of input-token ratios across datasets. It does not mean every question, dataset or model uses fewer tokens. For example, Table 1's Luna/HERB condition uses more input tokens with the map. Token use is also distinct from latency, total lifecycle cost and a tenant's billed consumption.

The candidate mechanism is material: rank entity pages with BM25, a lexical relevance method, pool their linked documents, rerank those documents and give the agent candidate titles, paths and IDs. It still chooses what to open and can search beyond the shortlist (Appendix B.3, pages 18 to 19). Simply adding entity pages to a library would reproduce only part of the tested design.

The experimental agent uses shell tools over files. A managed Microsoft retriever has different indexing, chunking, permissions and orchestration. The corpora are selected benchmark collections, with larger tests reaching 20,000 documents. They do not establish performance across an entire tenant. Most answer scores use model judges, although the paper includes another judge comparison and document recall has a deterministic component.

The preprint supplies enough evidence to justify a bounded prototype. It does not establish independently reviewed domain correctness, robust identity resolution on our sources, secure tenant deployment or production cost. Its ethics statement explicitly recognises that aggregated entity pages can reveal sensitive information and documents a user cannot access (page 10).

Implications for the existing OKF+ design

Here, OKF+ means the richer experimental bundle and evidence practices around OKF 0.2 and additive profiles. It is not a separate universal core standard. The current architecture plan, semantic contract and Bundle Wiki profile already make that distinction.

The strongest confirmation is of the bundle as reusable infrastructure between source documents and different AI clients. The strongest challenge is to any assumption that a richer graph or more generated prose automatically improves retrieval. A graph needs a task-specific interface and a relevant entry route.

Preserve three distinct kinds of information

An entity map answers where else this subject is mentioned. A governed semantic assertion answers what relationship a source or reviewed derivation supports. Evidence assembly answers whether the declared context needed for this question is present within the admitted scope. Their outputs should remain distinguishable in files, tools and the Reader.

For example, a mention of a project in a risk register creates a discovery route. It does not establish that the project has approval or that the risk caused a delay. Those claims need source evidence and, where represented as domain relationships, the existing assertion contract. A generated entity page must not turn an older status and a newer proposal into a single current fact.

The context engine currently resolves declared concepts and follows a bounded set of predicates. Its requirements checks run after traversal; requirements are not hidden retrieval seeds. A map should improve discovery without bypassing that contract. Newly found evidence must enter through a separately designed admission step or producer update. Discovery alone cannot turn an insufficient package into a sufficient one.

Add an optional navigation profile

Prototype a separately versioned profile before proposing any core change. The names below are design suggestions, not accepted schema fields or current Reader features.

Keep document membership as the primary map structure, matching the paper. Passage links are a useful OKF+ adaptation for precise reading; they should not silently replace the document's context with an isolated chunk. Retain single-document entities where useful for source identity, while distinguishing them from the recurring entities used to connect documents.

Prefer existing producer IDs, explicit references and reviewed aliases before introducing model-based resolution. Define how to distinguish an organisation from its team, a service from a service family, and a current body from its predecessor. Type catalogues can be informed by source sampling, but should be reviewed and versioned. Domain concepts without a neat named entity still need facets, semantic relationships and ordinary search.

Do not hand-edit canonical profile mirrors or repurpose skos:exactMatch or another domain predicate to mean co-mention. If a navigation association is published as a semantic assertion, it must meet the existing assertion requirements. Otherwise retain it as explicitly derived navigation metadata.

Bind the map and pages to exact source versions. On additions, changes, deletions, identity merges/splits or permission changes, invalidate all affected mentions, postings, pages and consumer projections. Preserve tombstones and replay identities where policy permits. Incremental addition experiments in the paper do not settle deletion or permission-revocation behaviour.

Using a bundle in Microsoft environments

Choose an integration route according to the required control over evidence. Microsoft 365 Copilot, Copilot Studio and a custom Azure application offer different retrieval and orchestration controls. Microsoft Graph is Microsoft's API and data platform; it does not automatically interpret an OKF+ semantic graph. The repository's authoring “Foundry” is also distinct from Microsoft Foundry.

First route through SharePoint and Copilot

Keep canonical authored sources and release identities in the existing governed process. Generate a Microsoft-facing document set: a collection overview, one readable record per useful source unit, and concise entity pages. Each derivative should carry its bundle ID, snapshot, stable record/entity ID, source version, source link, locator and review status. Entity pages should list the underlying source documents and preserve dates and disagreement.

Place one admitted snapshot in a deliberately scoped SharePoint library or folder. Exclude retired derivatives from the agent's active knowledge scope while retaining governed history elsewhere. Configure a dedicated agent with that source scope, a clear evidence task and instructions to inspect sources, state ambiguity and avoid filling gaps. Microsoft documents explicit SharePoint scoping for declarative agents; omitting the scope can make all user-accessible SharePoint/OneDrive content available. See adding knowledge to declarative agents.

This is a projection experiment. A link in an entity page does not prove the host will traverse it, read every source or preserve a qualification. Check indexing, actual citations and the source text observed in the response. A ZIP or JSON file is not evidence that a host understands OKF+ identities, shards, digests or semantic relationships.

The existing SharePoint trial reports 292 exact family selections from 293 authored development situations using generated Word records. The remaining case selected an existing broader neighbour. This supports the feasibility of useful Microsoft-facing derivatives, with a specific identity-resolution weakness. It does not test CorpusMap traversal, independent domain answers or cross-user access control. Use the same frozen records as a baseline and a new held-out question set.

Microsoft documents permission trimming for the signed-in user on the SharePoint knowledge route, alongside encryption and authentication limits. Apply those controls to the generated pages themselves; a restricted fact copied into a broadly readable page has already crossed the boundary. Check the exact tenant, channel, format and licence configuration against SharePoint knowledge guidance.

Preferred controlled route through Copilot Studio

Use Copilot Studio as the conversational client of an authenticated, read-only OKF service when the task needs explicit evidence selection. Microsoft documents Streamable HTTP MCP connections, API-key or OAuth authentication, and a custom-connector alternative. These capabilities provide an integration path; they do not prove the current Ask OKF service works in a particular tenant. See connecting an MCP server.

Reuse the existing service's compact manifest and verified read pattern. Add navigation as a separate capability: search entities and documents, inspect ambiguities, list a permitted entity neighbourhood, then read selected original evidence. Retain the option to search documents outside the map. A Microsoft adapter can use REST through a custom connector if the chosen client cannot reliably consume the MCP results.

The proposed query journey is:

1. Authenticate the user and establish the allowed corpus and current access.
2. Resolve candidate entities, exposing collisions rather than silently merging them. Rank relevant pages and then their linked documents.
3. Return a small shortlist with reasons and source identities. Let the agent request complementary evidence within explicit call and byte budgets.
4. Admit selected evidence through the governed assembly contract. Check required context, dates, scope, conflicting evidence and omissions.
5. Generate an explanation only from the admitted package. Retain its snapshot, map, engine and context identities and allow source inspection.

The current remote service serves approved immutable public OKF-DWP sources anonymously. Its three tool definitions do not provide general entity search or arbitrary document access. Hosting the code on Azure or adding a login would not make it a secure tenant-wide service. A restricted deployment needs server-side authorisation for every operation and a new admitted-source design.

Search and connector options

For a custom application, keep immutable bundle snapshots in approved storage and project searchable documents, entity pages and IDs into Azure AI Search. Implement entity postings in the service or a suitable data store. Search ranks candidates; the OKF service retains source verification, relationship meaning and dependency checks. Keep original document identity on every indexed passage so citations can return to the exact source version.

Azure AI Search now distinguishes generally available minimal extractive retrieval from preview LLM planning, answer synthesis and other capabilities. Pin the chosen API and feature set, rather than treating “agentic retrieval” as one readiness category. Microsoft also documents additional latency and separate Search and model charges. See the agentic retrieval overview. Its current knowledge-source matrix marks indexed/remote SharePoint, remote MCP and several Fabric integrations as preview. Use the source matrix when deciding which dependencies are acceptable.

An alternative is to generate Microsoft 365 Copilot connector items from the bundle. Each external item has its own stable item ID, metadata, searchable content and access control list. Project entity pages and source records as distinct items, retain their OKF IDs, and synchronise updates and deletions. Microsoft's external-item guidance defines this indexing contract. It does not import RDF semantics or make Copilot follow the map's paths.

Use Dataverse for reviewed mappings, ownership, review decisions and workflow state if these need a Power Apps interface. Keep source passages and immutable bundle versions separately governed. Any round trip must preserve IDs, provenance, rights, assertion status and unresolved identities. Fabric is an option when an existing analytics programme needs it; the paper supplies no reason to migrate the whole bundle estate there.

Permissions and information handling

An entity page aggregates knowledge. Protect its aliases, facts, document titles, neighbourhood counts and citations as well as its source text. Filtering only the final document download is too late.

For a first pilot, choose a corpus whose participants share the same access boundary. A static page assembled from mixed-permission sources must be restricted to users permitted to see every included contribution. For wider use, either maintain verified access partitions or construct pages at query time from currently authorised contributions. Apply filtering before ranking, summarisation and counts; partition caches by effective access policy and invalidate them when permissions change. Never trust group IDs supplied only in an agent prompt.

Preserve organisational sensitivity labels, retention requirements, source rights and permitted processing locations in the Microsoft projection design. An OKF rights statement is metadata, not access enforcement or permission to copy a source. Derived summaries can retain a source's restrictions. Include service logs, prompts, cached pages and retained answers in the handling plan. Treat source and tool text as untrusted data throughout.

Test two users with deliberately different access, including a restricted document that shares an entity with a public document. The less privileged user must not receive the restricted title, fact, alias, link or revealing count. Test revocation during an existing conversation and against a warm cache. The previous trial's absence of permission-related response text does not discharge these controls.

How to reshape the programme

The existing plan's priority of one dependable evidence journey remains sound. Add a bounded navigation experiment to its domain and client acceptance work, with the following order. These are proposed responsibilities to assign.

Start with synthetic or already admitted non-sensitive sources. A suggested pilot scale is 100 to 300 documents with deliberate overlaps and a held-out set of 40 to 60 independently written questions. These are manageable design choices, not numbers validated by the paper. Include a second source type and some unmapped documents so the test cannot succeed through entity pages alone.

Questions should require joining approval, requirements and current status; finding exceptions; distinguishing near-neighbour services; disambiguating identical names; handling historical versions; and recognising missing or inaccessible evidence. Freeze expected supporting documents and essential qualifications independently of the map builder. Reuse the existing A–H evaluation and add entity-resolution and map-navigation measures.

Report document recall, supporting-passage precision, false identity merges, unresolved rates, citation fidelity, qualification retention, completeness against declared requirements and specialist answer assessment separately. Also measure calls, bytes, input/output tokens where observable, latency and failures. If a managed client does not expose token use or model-visible context, record that measurement gap and use observed latency and tenant consumption; do not infer a saving from response length.

Adoption should require a pre-agreed improvement over the strongest baseline, with no false merge in the critical identity controls, no unauthorised disclosure and no loss of required qualifications. Zero failures on these controls is an acceptance gate for that trial, not a universal safety claim.

Cost and maintenance decisions

Count initial extraction, resolution, review, page generation, updates, permission synchronisation, hosting, Search, model use and operations. A cheap query can still be an expensive system. Table 4's construction estimates range widely by builder; its Luna upper bound of $74.65 applies to the paper's EnterpriseRAG-Bench setting, not to our corpus or Microsoft prices.

For a fixed evaluation period, compare:

map total = initial build + updates + hosting + governance + query count × mapped query cost

with the corresponding baseline total. A financial break-even exists only if the measured per-query saving exceeds any extra recurring cost at the expected volume. Include review effort and permission updates, and use tenant billing records for actual Microsoft charges. The historical SharePoint report's counterfactual prices are not a current deployment quote. Any metered pilot needs its own approved budget.

Keep larger graph rendering, unconstrained wiki synthesis, broad automatic entity linking and platform migration behind this evidence. The research supports making the existing knowledge easier to navigate and reuse. OKF+ should contribute the provenance, exact source identity and visible evidence limits that a navigation map alone cannot supply.

Evidence and decision boundaries

Paper findings above refer to the supplied v1 PDF, particularly sections 3 to 5, Tables 1 and 4, Appendix A, Appendix B.3/B.4 and the ethics statement. Microsoft capability descriptions were checked against the linked official documentation on 26 October 2026; availability, licensing and policy still depend on the selected tenant and deployment. The repository links describe the stated baseline and retained experiments. Proposed files, tools, pilot sizes and architecture choices in this review have not been implemented or tested by this review.