Triple
T2616158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Bull Arena (Leipzig) |
E58891
|
entity |
| Predicate | hasElectronicTicketing |
P41459
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Red Bull Arena (Leipzig), hasElectronicTicketing, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasElectronicTicketing Context triple: [Red Bull Arena (Leipzig), hasElectronicTicketing, yes]
-
A.
hasTicketing
Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
-
B.
usedInE-tickets
Indicates that something (such as a method, technology, or feature) is employed or applied within the context of electronic tickets (e-tickets).
-
C.
hasTicketInspection
Indicates that a ticket is checked or verified by an authorized inspector or system.
-
D.
ticketingCompatibleWith
Indicates that two systems, services, or components can interoperate or be used together within the same ticketing or reservation workflow without conflict.
-
E.
hasFareControlIntegrationSince
Indicates that a fare control system has been integrated with another system or entity starting from a specific point in time.
- F. None of above. chosen
Provenance (4 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_69ab4ac444dc819099614e534dd6021f |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd89325308190985598373eb0d296 |
completed | March 7, 2026, 7:49 a.m. |
| PD | Predicate disambiguation | batch_69abd80cd7fc81909e9696db2919129f |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd891bcd481909af5340a64ff69f9 |
completed | March 7, 2026, 7:49 a.m. |
Created at: March 6, 2026, 9:50 p.m.