Triple
T6450936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broadwood Stadium |
E139861
|
entity |
| Predicate | safetyCertificateCapacity |
P1931
|
FINISHED |
| Object | approximately 8000 |
—
|
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: approximately 8000 | Statement: [Broadwood Stadium, safetyCertificateCapacity, approximately 8000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyCertificateCapacity Context triple: [Broadwood Stadium, safetyCertificateCapacity, approximately 8000]
-
A.
hasSafetyCertificate
Indicates that an entity possesses or has been granted a valid safety certificate.
-
B.
cargoCapacityFeature
Indicates that an entity has a feature specifying how much cargo it can carry or accommodate.
-
C.
typicalCapacity
chosen
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
D.
hasSafetyCharacteristic
Indicates that an entity possesses a specific safety-related property, feature, or attribute.
-
E.
designedCargoCapacity
Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
- 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_69c008b301948190a35854e5284dc822 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069b4171c8190b0acad78700998ed |
completed | March 22, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69c0673b44148190aed70084f0ff4992 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:47 p.m.