Triple
T14927655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montpelier railway station |
E372172
|
entity |
| Predicate | hasPrimaryTractionType |
P5678
|
FINISHED |
| Object | diesel multiple unit |
—
|
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: diesel multiple unit | Statement: [Montpelier railway station, hasPrimaryTractionType, diesel multiple unit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryTractionType Context triple: [Montpelier railway station, hasPrimaryTractionType, diesel multiple unit]
-
A.
usedTractionType
Indicates the type of traction or drive mechanism that was employed in performing the action or operating the entity.
-
B.
currentTractionType
Indicates the type or mode of traction currently being applied or in use in a given context.
-
C.
primaryTraction
chosen
Indicates that one entity serves as the main source or means of traction, pulling power, or driving force for another entity or process.
-
D.
hasPrimaryTrafficType
Indicates that an entity is associated with a main or predominant type of traffic it handles or is designed for.
-
E.
hasPrimaryTransportationMode
Indicates the main or most frequently used mode of transportation associated with an 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded634e67881909daec9eaef188d09 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:35 a.m.