Triple
T16470785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 5MT |
E400052
|
entity |
| Predicate | locomotiveTypeContext |
P122912
|
FINISHED |
| Object | tender 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: tender locomotives | Statement: [5MT, locomotiveTypeContext, tender locomotives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locomotiveTypeContext Context triple: [5MT, locomotiveTypeContext, tender locomotives]
-
A.
laterLocomotiveType
Indicates that one locomotive type succeeds or comes after another in time, representing a later development or version in locomotive design.
-
B.
primaryLocomotiveType
Indicates the main method or mechanism by which an entity typically moves or travels.
-
C.
typicalLocomotiveClass
Indicates that one locomotive class is the standard or most commonly used class for a given context, operator, or service.
-
D.
locomotiveConfiguration
Indicates the specific arrangement and type of power and running units (e.g., wheel or axle layout) that define how a locomotive is configured.
-
E.
hasLocomotive
Indicates that one entity possesses or is equipped with a locomotive as part of its composition or operation.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32dd0d2fc81909b68b5afb00f192f |
completed | April 18, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69e22706b0588190a48a951c5211a617 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24556c1348190902a4d116c3137d9 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:11 a.m.