Triple
T34888537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montreal–Quebec City |
E1006216
|
entity |
| Predicate | hasCommonTravelTimeByTrainHours |
—
|
GENERATED |
| Object | about 3 to 3.5 |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonTravelTimeByTrainHours Context triple: [Montreal–Quebec City, hasCommonTravelTimeByTrainHours, about 3 to 3.5]
-
A.
railTravelTimeRangeHours
chosen
Indicates the range of time, in hours, that a journey by rail between the related entities is expected to take.
-
B.
railwayTimeUsage
Indicates how much time is spent using or operating a railway within a given context or period.
-
C.
hasApproximateFastRailJourneyTimeHours
Indicates that there is an estimated duration, measured in hours, for a fast rail journey between the related entities.
-
D.
hasNightTrainService
Indicates that a transportation route or station is served by trains that operate during nighttime hours.
-
E.
hasRegionalTrainService
Indicates that a location or route is served by regional train services connecting it to nearby areas.
- F. None of above.
Provenance (1 batch)
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_69f76dbedb288190afe5780710847410 |
completed | May 3, 2026, 3:46 p.m. |
Created at: May 3, 2026, 4 p.m.