Triple
T27124233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Carolina Transportation Museum |
E687079
|
entity |
| Predicate | hasRailroadEquipment |
P12267
|
FINISHED |
| Object | steam locomotives |
—
|
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: steam locomotives | Statement: [North Carolina Transportation Museum, hasRailroadEquipment, steam locomotives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailroadEquipment Context triple: [North Carolina Transportation Museum, hasRailroadEquipment, steam locomotives]
-
A.
hasRail
Indicates that something is equipped with, includes, or is connected to a rail or rail system.
-
B.
hasRackRailway
Indicates that one entity possesses or includes a rack railway system connecting locations or operating within its area.
-
C.
usesRollingStock
Indicates that one entity employs or operates specific rolling stock (such as rail vehicles) in its activities or services.
-
D.
hasRailwayTraction
Indicates that a railway system, line, or vehicle uses a specified type or method of traction (e.g., electric, diesel, steam) for its propulsion.
-
E.
hasLocomotive
chosen
Indicates that one entity possesses or is equipped with a locomotive as part of its composition or operation.
- 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_69ef148c2b588190afc15b529f7af845 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 27, 2026, 9 a.m.