Triple
T1140300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bombardier Voyager family |
E23434
|
entity |
| Predicate | trainConfiguration |
P26476
|
FINISHED |
| Object | 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: multiple unit | Statement: [Bombardier Voyager family, trainConfiguration, multiple unit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainConfiguration Context triple: [Bombardier Voyager family, trainConfiguration, multiple unit]
-
A.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
B.
railServiceType
Indicates the specific category or type of rail service that applies to the relationship between the involved entities (e.g., local, express, freight).
-
C.
trainsForOccupation
Indicates that an entity undergoes training or preparation aimed at qualifying for or performing a specific occupation.
-
D.
trainOperator
Indicates that one entity operates, manages, or runs train services for another entity or within a specific rail system.
-
E.
railSystemType
Indicates the specific category or classification of a rail transportation system that an entity belongs to or operates within.
- 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_69a493ef399c8190b04b9146d2314f59 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bde18d208190848c189b2b8d585f |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4b52d48190bec2e7ad1cc8efc0 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bddfa598819088690e1ab010ba0b |
completed | March 1, 2026, 10:29 p.m. |
Created at: March 1, 2026, 7:44 p.m.