Triple
T6649490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allianz Stadium |
E150783
|
entity |
| Predicate | sponsorshipNameStart |
P40278
|
FINISHED |
| Object | 2017 |
—
|
LITERAL 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: 2017 | Statement: [Allianz Stadium, sponsorshipNameStart, 2017]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sponsorshipNameStart Context triple: [Allianz Stadium, sponsorshipNameStart, 2017]
-
A.
sponsorshipName
Indicates the name or title associated with a sponsorship relationship between entities.
-
B.
sponsorshipNameSince
chosen
Indicates the date or time from which a particular sponsorship name has been in effect for the associated entity or relationship.
-
C.
sponsorshipNameAdopted
Indicates that an entity has adopted or taken on a specific sponsorship name as its official or recognized designation.
-
D.
sponsorshipDealStart
Indicates the point in time when a sponsorship agreement between parties officially begins.
-
E.
sponsoredNameHolder
Indicates that one entity holds or uses a name or title under the sponsorship or endorsement of another entity.
- F. None of above.
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_69c687f2c9508190a60b9aad31d3f358 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6ad04d66c8190926ffcbff372643b |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:01 p.m.