Triple
T4936884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Route 24E |
E110832
|
entity |
| Predicate | hasRollingStockColor |
P48066
|
FINISHED |
| Object | yellow |
—
|
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: yellow | Statement: [Route 24E, hasRollingStockColor, yellow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRollingStockColor Context triple: [Route 24E, hasRollingStockColor, yellow]
-
A.
rollingStockColor
chosen
Indicates the color attribute assigned to a piece of rolling stock (such as a rail vehicle) in the relationship.
-
B.
usesRollingStockBrand
Indicates that one entity employs or operates rolling stock manufactured under a specific brand.
-
C.
usesRollingStock
Indicates that one entity employs or operates specific rolling stock (such as rail vehicles) in its activities or services.
-
D.
ownedRollingStock
Indicates that one entity possesses or has ownership rights over specific rolling stock (such as trains, railcars, or locomotives).
-
E.
hasRollingStockOnDisplay
Indicates that a location or entity has railway rolling stock (such as locomotives or carriages) exhibited for public viewing.
- 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7085b1dc819099408f6503f0210f |
completed | March 20, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69bd6c389b9881908ad7fb1c5393c1b1 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:30 p.m.