---
title: "KB completeness has a formal toolkit beyond obligatory attributes — cardinality assertions, the No-Change Assumption, and text-extraction recall"
type: "claim"
status: "budding"
audit_status: "capture-verified (ar5iv full-text read at capture level, 2026-07-01; quotes carried from that direct read)"
source_url: "https://arxiv.org/abs/2305.05403"
source_title: "Completeness, Recall, and Negation in Open-World Knowledge Bases: A Survey"
source_author: "Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian Suchanek"
source_date: "2023-05-09T00:00:00.000Z"
source_tier: 1
source_quote: "Completeness of a KB can be assessed by comparing the cardinality of a relation with the real cardinality"
provenance: "Promotion from 10-inbox/raw/2026-07-01-razniewski-2023-completeness-mechanisms-...md, 2026-07-07, queen cycle 6"
origin: "session"
date_created: "2026-07-07T00:00:00.000Z"
tags: ["knowledge-graph","completeness","cardinality","gap-detection","PKM"]
---


The same survey that grounds [[claim-obligatory-attributes-as-gap-signal]]
offers three further completeness instruments, each mappable to vault
practice:

1. **Cardinality assertions** — comparing a relation's recorded cardinality
   against its real one is the formal primitive of completeness measurement.
   Vault analogue: "this cluster should have N members" claims (a MOC that
   names five clusters but links four is measurably incomplete).
2. **No-Change Assumption (NCA)** — if repeated observations stop adding new
   facts, treat the region as converged: a lightweight temporal completeness
   signal. Vault analogue: a topic whose captures stop yielding new claims
   has stopped growing — the loop-until-dry intuition, formalized.
3. **Text-extraction-based recall** — compare what a source document mentions
   against what the KB extracted from it. Vault analogue: the promotion
   accounting's `not_promoted` lists exist precisely so recall against a
   capture is auditable.

One quantitative boundary from the paper stays flagged per the capture: the
LM-KBC 2023 best-system figure (69% F1 on cardinality prediction) is cited
within the survey from shared-task proceedings — [unverified-quant — needs
primary] until read there. See [[question-gap-detection]],
[[moc-machine-self-knowledge]].