Triple
T13972891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stadium MK |
E336107
|
entity |
| Predicate | hasHospitality |
P22897
|
FINISHED |
| Object | executive boxes |
—
|
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: executive boxes | Statement: [Stadium MK, hasHospitality, executive boxes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHospitality Context triple: [Stadium MK, hasHospitality, executive boxes]
-
A.
hasHospitalityComponent
chosen
Indicates that something includes, involves, or is associated with a hospitality-related element, service, or function.
-
B.
hasAccommodation
Indicates that an entity provides, owns, or is associated with a place for someone to stay or live.
-
C.
hospitalityContext
Indicates a situational or environmental setting in which hospitality-related interactions, services, or behaviors occur.
-
D.
hasResortHotel
Indicates that one entity owns, includes, or is associated with a resort hotel as part of its facilities or offerings.
-
E.
hadStationHotel
Indicates that a railway station possessed or was associated with a hotel facility serving its passengers or operations.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8fd6d48190a157eae8df3a2f3a |
completed | April 14, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69dd465a21408190b912a42c50ffa0d9 |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.