Triple
T28428781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Pudong Football Stadium |
E715061
|
entity |
| Predicate | hasHospitalityArea |
P22897
|
FINISHED |
| Object | corporate hospitality suites |
—
|
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: corporate hospitality suites | Statement: [Shanghai Pudong Football Stadium, hasHospitalityArea, corporate hospitality suites]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHospitalityArea Context triple: [Shanghai Pudong Football Stadium, hasHospitalityArea, corporate hospitality suites]
-
A.
hasHospitalityComponent
chosen
Indicates that something includes, involves, or is associated with a hospitality-related element, service, or function.
-
B.
hasRestaurantArea
Indicates that a place or establishment includes a designated area used as a restaurant or for dining services.
-
C.
hasRegionalAmenity
Indicates that a region provides or contains a specific amenity or facility within its area.
-
D.
hasRoomService
Indicates that a lodging or accommodation offers room service as an available amenity or feature.
-
E.
hasReservationArea
Indicates that an entity is assigned or associated with a specific reserved area or section designated for its use.
- 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_69efd6b253888190b3c7222ed6a403a8 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 28, 2026, 1:38 a.m.