Triple
T10735216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GP40PH-2 |
E253177
|
entity |
| Predicate | roleInTrain |
P95715
|
FINISHED |
| Object | road locomotive |
—
|
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: road locomotive | Statement: [GP40PH-2, roleInTrain, road locomotive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInTrain Context triple: [GP40PH-2, roleInTrain, road locomotive]
-
A.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
-
B.
portraysTrainAs
Indicates that one entity represents or depicts a train in a particular way or role.
-
C.
providesTrainingFor
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
D.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
E.
trainedAs
Indicates that one entity has received education or instruction to perform the role, profession, or function represented by another entity.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d71021cccc8190ba2d3bbd7d50e2a7 |
completed | April 9, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69d6f309a44881908e49e3ba478c35b4 |
completed | April 9, 2026, 12:30 a.m. |
| PDg | Predicate description generation | batch_69d6fa323564819097b207eb53f8a9b8 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:14 p.m.