Triple
T10416588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aegon Hungary |
E245532
|
entity |
| Predicate | parentOrganization |
P254
|
FINISHED |
| Object | Aegon N.V. |
E245526
|
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: Aegon N.V. | Statement: [Aegon Hungary, parentOrganization, Aegon N.V.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aegon N.V. Context triple: [Aegon Hungary, parentOrganization, Aegon N.V.]
-
A.
Aegon N.V.
chosen
Aegon N.V. is a multinational life insurance, pensions, and asset management company headquartered in the Netherlands.
-
B.
Aegon UK
Aegon UK is a British financial services company that provides pensions, investments, and insurance products as part of the global Aegon group.
-
C.
Egis Group
Egis Group is a global engineering and infrastructure consulting firm that manages and operates transportation facilities such as airports, roads, and urban transit systems.
-
D.
Aegon Asset Management
Aegon Asset Management is a global investment management company that provides a range of asset management services to institutional and individual investors.
-
E.
Royal Vopak
Royal Vopak is a Dutch multinational tank storage company that specializes in storing and handling liquid bulk products such as chemicals, oil, gases, and biofuels at terminals worldwide.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea108fec8190819423630888fa2b |
completed | April 7, 2026, 11:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90d92510481909135a75b2f582795 |
completed | April 10, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:10 p.m.