Triple
T3967253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saratoga Race Course |
E92245
|
entity |
| Predicate | grandstandType |
P42382
|
FINISHED |
| Object | open-air grandstand |
—
|
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: open-air grandstand | Statement: [Saratoga Race Course, grandstandType, open-air grandstand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grandstandType Context triple: [Saratoga Race Course, grandstandType, open-air grandstand]
-
A.
hasGrandstandFeature
chosen
Indicates that something possesses or includes a grandstand-related feature or characteristic.
-
B.
bandstandStyle
Indicates the architectural or design style characterizing a particular bandstand.
-
C.
stadiumFeature
Indicates that a stadium possesses or includes a particular feature, characteristic, or facility.
-
D.
stadium
Indicates that an entity is a sports or event venue where games, competitions, or large gatherings take place.
-
E.
spectatorAreaType
Indicates the specific kind or category of area designated for spectators in a venue or event setting.
- 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaca33e4819091957c7915857a42 |
completed | March 9, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69aef8f252b081909749d40440d372b2 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:32 p.m.