Triple
T22356860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phoenix Raceway |
E552674
|
entity |
| Predicate | grandstandCapacityApprox |
P103582
|
FINISHED |
| Object | 42000 |
—
|
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: 42000 | Statement: [Phoenix Raceway, grandstandCapacityApprox, 42000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grandstandCapacityApprox Context triple: [Phoenix Raceway, grandstandCapacityApprox, 42000]
-
A.
stadiumCapacityApprox
Indicates an approximate number of people that a stadium can accommodate.
-
B.
venueCapacityApproximate
chosen
Indicates an approximate or estimated capacity of a venue in terms of how many people it can accommodate.
-
C.
standingCapacity
Indicates the maximum number of people that are allowed or able to stand in a given space or vehicle.
-
D.
hasGrandstandFeature
Indicates that something possesses or includes a grandstand-related feature or characteristic.
-
E.
audienceCapacityType
Indicates the classification or type of capacity used to describe how many audience members a venue or event space can accommodate.
- 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_69e11e4a0ad08190a385b4d343cf6524 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157d08b148190a9a4e445e8579219 |
completed | April 29, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69e7300c20088190a59e5bf9e70384f3 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:44 p.m.