Triple
T36269243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford ½-ton pickup (prewar car-based design) |
E892621
|
entity |
| Predicate | cargoCapacityClass |
P18218
|
FINISHED |
| Object | ½-ton payload class |
—
|
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: ½-ton payload class | Statement: [Ford ½-ton pickup (prewar car-based design), cargoCapacityClass, ½-ton payload class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cargoCapacityClass Context triple: [Ford ½-ton pickup (prewar car-based design), cargoCapacityClass, ½-ton payload class]
-
A.
cargoCapacityFeature
Indicates that an entity has a feature specifying how much cargo it can carry or accommodate.
-
B.
designedCargoCapacity
chosen
Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
-
C.
cargoCapacityConfigurable
Indicates that the cargo capacity of an entity can be adjusted or configured rather than being fixed.
-
D.
slingLoadCapacity
Indicates the maximum weight or load that can be safely carried or supported using a sling.
-
E.
passengerCapacityCategory
Indicates the classification of an entity based on the number of passengers it is designed or allowed 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_69f76e488f34819083e254dbe288c27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7ba6d06f48190a71b5a2f19e2232f |
completed | May 3, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:09 p.m.