Triple
T660645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UPP |
E11745
|
entity |
| Predicate | railroadReportingMarkType |
P1305
|
FINISHED |
| Object | passenger equipment |
—
|
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: passenger equipment | Statement: [UPP, railroadReportingMarkType, passenger equipment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railroadReportingMarkType Context triple: [UPP, railroadReportingMarkType, passenger equipment]
-
A.
railroadClass
Indicates the classification or category of a railroad according to an established system (e.g., by size, revenue, or regulatory status).
-
B.
rollingStockType
chosen
Indicates the specific category or type of railway rolling stock associated with an entity (e.g., locomotive, passenger car, freight wagon).
-
C.
railwayLineType
Indicates the specific kind or classification of a railway line associated with an entity (e.g., main line, branch line, high-speed line).
-
D.
markType
Indicates the specific category or kind of mark associated with or applied to an entity.
-
E.
usesRailGauge
Indicates that one entity (typically a railway system or line) operates using the specified rail gauge measurement of the other 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0f55f7481909e052a25bd12d455 |
completed | March 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69a49d1406ec8190abf546549264c85d |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.