Triple
T14458578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruutu |
E358520
|
entity |
| Predicate | parentOrganization |
P254
|
FINISHED |
| Object | Sanoma |
E356531
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Sanoma | Statement: [Ruutu, parentOrganization, Sanoma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanoma Context triple: [Ruutu, parentOrganization, Sanoma]
-
A.
Sanoma
chosen
Sanoma is a major Finnish media and learning company known for its newspapers, magazines, digital media, and educational publishing across Europe.
-
B.
Bonnier Group
Bonnier Group is a major Swedish family-owned media conglomerate with interests in publishing, broadcasting, and digital media across multiple countries.
-
C.
Egmont Group
Egmont Group is an international network of national financial intelligence units that collaborate to combat money laundering, terrorist financing, and other financial crimes.
-
D.
Egmont Group
Egmont Group is a Danish media conglomerate and charitable foundation that operates in publishing, film, television, and digital entertainment across multiple countries.
-
E.
Ringier
Ringier is a Swiss-based international media company that owns and operates a wide portfolio of newspapers, magazines, digital platforms, and entertainment brands across multiple countries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91aabebc819097eb61b2d81c9a91 |
completed | April 14, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd64935d8081908e5b0e80027948e0 |
completed | May 8, 2026, 4:20 a.m. |
Created at: April 10, 2026, 1:19 a.m.