Triple
T1422810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Pacific Cab Forward locomotive |
E30261
|
entity |
| Predicate | typicalWheelArrangement |
P5627
|
FINISHED |
| Object | 4-8-8-2 |
—
|
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: 4-8-8-2 | Statement: [Southern Pacific Cab Forward locomotive, typicalWheelArrangement, 4-8-8-2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWheelArrangement Context triple: [Southern Pacific Cab Forward locomotive, typicalWheelArrangement, 4-8-8-2]
-
A.
wheelArrangementSystem
chosen
Indicates the specific configuration or system by which the wheels of a vehicle or rolling stock are arranged and organized.
-
B.
numberOfWheels
Indicates the quantity of wheels that an entity possesses or is associated with.
-
C.
rollingStockType
Indicates the specific category or type of railway rolling stock associated with an entity (e.g., locomotive, passenger car, freight wagon).
-
D.
vehicleLayout
Indicates how the components or seating within a vehicle are arranged or configured relative to each other.
-
E.
wheelType
Indicates the specific kind or category of wheel associated with an entity.
- 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_69a498fb823c8190a67ce4c4837e641a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c52e4ed881908d85e0cb9fe851ac |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c4752abc8190a33b634c4d6fad28 |
completed | March 1, 2026, 10:57 p.m. |
Created at: March 1, 2026, 8 p.m.