Chimera
A graph of actors with profiles and the links between them, tied to the news. Its own graph engine.
- Good for
- A graph of the people and organisations in the news, with profiles that refresh themselves when a name spikes, for anyone who wants to see who is tied to whom.
- Measured
- Bad aliases from an automatic merge, once on about 1 actor in 13, cleaned up twice in September; the path that caused them is closed.
- Six large state actors with reviewed profiles, locked against overwriting.
- Open questions
- Can every profile be traced back to the articles behind it?
- When a profile changes, would a careful reader agree with the change?
Chimera
One dot, 5 actors. Grey: actors that arrived from the news and are waiting to be classified.
Persons are the largest kind, with 4,953. 6,671 newer actors are still waiting to be classified; 58 percent of them arrived since September.
22,146 actors in 17 kinds, 84,686 links between them.
Source: Chimera actor graph, read at the moment of the snapshot
Measured 4 Nov 2026, 13:04 UTC
What Chimera keeps
- Actor. A state, person, organisation, company, group, place, event or asset, with a type and aliases.
- Relations. To other actors, weighted by how often they appear together in the news.
- Profile. Where there is enough material, written by a local language model: motivations, traits, leverage points.
Chimera keeps the actors: states, people, organisations, companies, groups, places, events, assets. Each one has a type, aliases, and relations to other actors, weighted by how often they appear together in the news. Where there is enough material, a local language model writes a profile: motivations, traits, leverage points.
Where the actors come from
- Retina. Every entity the news pipeline extracts becomes a candidate.
- Spike. A spike around a name triggers a fresh profile.
- Graph. An embedded engine, switched over on 31 May 2026.
- 53
- links that could be drawn both ways between the registers and the news actors, measured in July. The join is parked.
The graph runs on an embedded engine chosen for the purpose and switched over on 31 May 2026. Actors arrive from Retina: every entity the news pipeline extracts becomes a candidate, and a spike around a name triggers a fresh profile. Ownership and sanctions registers sit alongside, several hundred thousand edges, but they barely touch the news actors: measured in July, 53 links could be drawn both ways. That join is parked, not built.
What is not yet there
- about 1 in 13
- actors carried another actor's name as an alias after an automatic merge
- two
- clean-ups in September; the path that caused it is closed
- 84
- confirmed same-actor links, not grown since 1 September
- 6
- large state actors with reviewed profiles, locked against overwriting
What is not yet there, stated plainly. A profile cannot be traced back to the news articles behind it; the pipeline does not keep that link, and a checking tool cannot either. Where a web search fed a profile, the page addresses are kept. An automatic merge once left about one actor in thirteen carrying another actor’s name as an alias; two clean-ups in September went after them, and the path that caused it is closed. A layer of confirmed same-actor links holds 84 entries and has not grown since 1 September. Six large state actors have been curated by hand and are locked against automatic overwriting. The numbers below are read from the running system on the day of the snapshot; the graph grows while you read.
What goes in
Snapshot 4 November 2026Actors arrive from Retina: every entity the news pipeline extracts becomes a candidate. What the graph adds is structure: a type, aliases, relations to other actors weighted by how often they appear together, and, for 14,435 of the 22,146, a profile written by a local model.
Actors by type
- not yet typed6,671
- people4,953
- cities2,149
- organisations1,997
- companies1,639
- regions1,046
- assets1,034
- events850
- institutions648
- countries302
- concepts298
- groups151
- platforms132
- media outlets120
"Not yet typed" is honest: 6,671 actors are in the graph but have not been classified.
Relations
- relates72,476
- expressed5,006
- about5,006
- mentions2,198
Bars on a log scale. "Relates" is co-mention in the news; "expressed" and "about" carry stances; "mentions" links to articles.
What comes out
Most connected actors
| actor | type | relations |
|---|---|---|
| United States | country | 353 |
| Russia | country | 158 |
| China | country | 153 |
| Iran | country | 143 |
| Israel | country | 128 |
| Philippines | country | 121 |
| Ukraine | country | 107 |
| Turkey | country | 85 |
| Palestinians | group | 63 |
| Democratic Party | party | 46 |
| Venezuela | country | 45 |
| Hamas | group | 38 |
| Pakistan | country | 37 |
| African National Congress | party | 33 |
| Android | platform | 32 |
| Press TV | media | 31 |
One actor and its neighbourhood: United States
The strongest relations of a single actor, weight from co-mention in the news.
- United Nations1.00
- UNESCO1.00
- International Energy Agency1.00
- ASIC1.00
- G71.00
- G201.00
- United Nations Security Council1.00
- IEA1.00
- World Meteorological Organization1.00
- OECD1.00
- Interpol1.00
- NATO1.00
- OECD1.00
- UN Security Council1.00
- Organisation for the Prohibition of Chemical Weapons1.00
- Security Council1.00
- Organization of American States1.00
- World Trade Organization1.00
One type at a time
The bar chart above is a headcount. This is what each type actually contains: the best connected actors of that type, with the number of relations behind each name, and for the leading one the relations themselves.
people
4,953 in the graph- Mark Rutte12
- Michael Schumacher7
- Rima Hassan7
- Carsten Breuer0
- Florian Seibel0
Strongest relations of Mark Rutte
- Rutte · not yet typed0.1386
- NATO · institutions0.0463
- Kaliningrad · cities0.0307
- Radev · people0.0281
- Münster · cities0.0266
- Tallinn · cities0.026
cities
2,149 in the graph- Hamburg23
- Palo Alto16
- Houston15
- Renk8
- Kandahar8
Strongest relations of Hamburg
- Hannover · cities0.1161
- Deutsche Bahn · companies0.1147
- Federal Minister of Transport · people0.0916
- Cologne · cities0.0822
- Nord Stream · assets0.0498
- Frankfurt am Main · cities0.0441
organisations
1,997 in the graph- International Rescue Committee9
- International Council on Ethics0
- Pharmaceuticals Action Committee0
- Humanitarian Needs Response Platform0
- GREDO0
Strongest relations of International Rescue Committee
- Wale Osofisan · people0.075
- IRC · organisations0.0588
- International Committee of the Red Cross · organisations0.0108
- UNFPA · institutions0.0084
- Ebola · concepts0.0078
- OCHA · organisations0.006
companies
1,639 in the graph- Shell14
- Workday13
- AI21 Labs11
- Bain Capital10
- WisdomTree9
Strongest relations of Shell
- TotalEnergies · companies0.0984
- NUPRC · not yet typed0.0614
- ExxonMobil · companies0.0599
- Kashagan · regions0.0571
- Nigerian National Petroleum Corporation · companies0.0528
- QatarEnergy · companies0.0465
regions
1,046 in the graph- Krasnodar Krai16
- Kurdistan14
- West Kordofan11
- Poltava Oblast10
- Central Africa9
Strongest relations of Krasnodar Krai
- UKMT Office for Talent and Opportunity · organisations0.2944
- Jubail · not yet typed0.1831
- Emirati · not yet typed0.177
- Mein Schiff 3 · assets0.1558
- MSC VICTORINE · not yet typed0.1443
- Teng-e Hormoz · not yet typed0.1344
assets
1,034 in the graph- Shahed10
- Trove Token0
- Pendle Token0
- AAVE Token0
- Mina Al-Ahmadi Oil Refinery0
Strongest relations of Shahed
- Ukrainian Air Force · not yet typed0.0585
- Millerovo · cities0.0554
- Crimea · regions0.0502
- Kursk · cities0.0476
- Iskander-M · assets0.045
- Donetsk Oblast · regions0.0439
events
850 in the graph- Iran War8
- China Development Forum0
- Karachi Fire0
- US-Israeli-Iran Conflict0
- Ukraine EU Accession0
Strongest relations of Iran War
- Länder · regions0.0198
- Bund · not yet typed0.0145
- Zorn · not yet typed0.0118
- Katherina Reiche · not yet typed0.0117
- Rehlinger · people0.0114
- Banaszak · not yet typed0.0114
institutions
648 in the graph- Cybersecurity and Infrastructure Security Agency18
- Security Service of Ukraine15
- Kommando Cyber- und Informationsraum0
- Executive Branch of the United States Government0
- Royal Arsenal of Woolwich0
Strongest relations of Cybersecurity and Infrastructure Security Agency
- Citrix · companies0.1424
- NetScaler · companies0.1369
- Ivanti · companies0.1111
- Fortinet · companies0.1007
- CISA · institutions0.0904
- Check Point Software Technologies · companies0.0889
countries
302 in the graph- United States353
- Russia158
- China153
- Iran143
- Israel128
concepts
298 in the graph- Transatlantic0
- Humanitarian Situation Monitoring0
- Pig Butchering0
- Garrison Towns0
- Shai-Hulud0
groups
151 in the graph- Palestinians63
- Hamas38
- Hezbollah29
- Kurds20
- Russian Athletes18
platforms
132 in the graph- Android32
- Kick25
- TikTok21
- Uniswap18
- npm15
media outlets
120 in the graph- Press TV31
- Al-Mayadeen27
- Forbes17
- Bloomberg16
- Axios13
parties
114 in the graph- Democratic Party46
- African National Congress33
- CDU29
- Alternative for Germany28
- BSW21
movements
35 in the graph- Kirchneristas25
- Movement23
- Israel Free13
- Slowtech13
- MAGA10
Two things this does not claim. The relation type is almost always RELATES, which means "appeared together in the same reporting", not a stated link between the two. And the quality varies by type: for an aid organisation the relations read like a sector map, for others they are looser. Shown as measured, not curated. Examples are drawn from actors that carry a profile, so a type with many entries can still show few.