Triple
T2601370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mercedes-Benz Arena (Stuttgart) |
E58349
|
entity |
| Predicate | hasHospitalityBoxes |
P26950
|
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: [Mercedes-Benz Arena (Stuttgart), hasHospitalityBoxes, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHospitalityBoxes Context triple: [Mercedes-Benz Arena (Stuttgart), hasHospitalityBoxes, yes]
-
A.
hasHospitalityComponent
Indicates that something includes, involves, or is associated with a hospitality-related element, service, or function.
-
B.
hasVIPBoxes
chosen
Indicates that an entity provides or contains VIP boxes as part of its facilities or offerings.
-
C.
hasPeriodRooms
Indicates that an entity contains rooms that are decorated or preserved to reflect specific historical periods.
-
D.
hasBackstageFacilities
Indicates that a venue or location provides backstage areas and related facilities for performers or staff.
-
E.
hasConcessions
Indicates that one entity provides or contains concession facilities, services, or rights (such as food, drink, or merchandise sales) for another entity or within a given context.
- 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_69ab4ac14040819098b13f4a27d5c8ff |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd4587014819089f78e93adf2144c |
completed | March 7, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69abd0d4e8648190b612eb09aa085451 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.