Triple
T1108850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tin Lizzie |
E25545
|
entity |
| Predicate | associatedWithWheelbase |
P4167
|
FINISHED |
| Object | about 100 inches |
—
|
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: about 100 inches | Statement: [Tin Lizzie, associatedWithWheelbase, about 100 inches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithWheelbase Context triple: [Tin Lizzie, associatedWithWheelbase, about 100 inches]
-
A.
wheelbase
chosen
Indicates the distance between the centers of the front and rear wheels of a vehicle.
-
B.
wheelType
Indicates the specific kind or category of wheel associated with an entity.
-
C.
associatedVehicleWeightClass
Indicates the weight classification category that is linked or assigned to a particular vehicle.
-
D.
numberOfWheels
Indicates the quantity of wheels that an entity possesses or is associated with.
-
E.
wheelArrangementSystem
Indicates the specific configuration or system by which the wheels of a vehicle or rolling stock are arranged and organized.
- 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9e6134481909f348986a25f65c6 |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b749e2a881909ef28745a7d2d917 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:43 p.m.