Triple
T5208290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allianz |
E117565
|
entity |
| Predicate | subsidiary |
P258
|
FINISHED |
| Object | Allianz Life |
E117565
|
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: Allianz Life | Statement: [Allianz, subsidiary, Allianz Life]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Allianz Life Context triple: [Allianz, subsidiary, Allianz Life]
-
A.
Allianz
chosen
Allianz is a leading global financial services company, best known as one of the world’s largest insurance and asset management providers.
-
B.
American Financial Group
American Financial Group is a large U.S. insurance and financial services holding company known for its specialty property and casualty insurance operations.
-
C.
Lincoln Financial Group
Lincoln Financial Group is a major American financial services company offering insurance, retirement, and investment products.
-
D.
Northwestern Mutual
Northwestern Mutual is a major American financial services and insurance company known for its life insurance, investment, and wealth management products.
-
E.
Prudential Financial
Prudential Financial is a major American financial services company best known for its life insurance, investment management, and retirement-related products.
- 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_69bd4463dd3c81909966123f20b79d57 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a6d70d081908c74e86b3bca9ba2 |
completed | March 20, 2026, 4:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beefd4b75c8190b1b87b8d93925245 |
completed | March 21, 2026, 7:21 p.m. |
Created at: March 20, 2026, 1:47 p.m.