Triple
T4568938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museum of the American Railroad |
E122980
|
entity |
| Predicate | hasRollingStockOnDisplay |
P57756
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Museum of the American Railroad, hasRollingStockOnDisplay, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRollingStockOnDisplay Context triple: [Museum of the American Railroad, hasRollingStockOnDisplay, yes]
-
A.
usesRollingStock
Indicates that one entity employs or operates specific rolling stock (such as rail vehicles) in its activities or services.
-
B.
ownedRollingStock
Indicates that one entity possesses or has ownership rights over specific rolling stock (such as trains, railcars, or locomotives).
-
C.
hasAircraftOnDisplay
Indicates that an entity exhibits or presents an aircraft as part of a display or collection.
-
D.
usesRollingStockCompatibleWith
Indicates that one entity operates using rolling stock that is technically and operationally compatible with the rolling stock standards or systems associated with another entity.
-
E.
usesRollingStockBrand
Indicates that one entity employs or operates rolling stock manufactured under a specific brand.
- F. None of above. chosen
Provenance (4 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58a0dfbc81909b5023f0c29addaf |
completed | March 20, 2026, 2:24 p.m. |
| PD | Predicate disambiguation | batch_69bd5227063c8190973155a875b013a7 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56f6e75481909c487a94a2c2d0ba |
completed | March 20, 2026, 2:17 p.m. |
Created at: March 20, 2026, 1:10 p.m.