Triple
T34109933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyaung U Airport |
E874810
|
entity |
| Predicate | hasPrimaryPassengers |
—
|
GENERATED |
| Object | tourists visiting Bagan |
—
|
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: hasPrimaryPassengers Context triple: [Nyaung U Airport, hasPrimaryPassengers, tourists visiting Bagan]
-
A.
hasThroughPassengersWith
Indicates that two transportation segments, services, or locations are connected by passengers who travel through them without starting or ending their journey there.
-
B.
hasPassengerRole
Indicates that an entity participates in a context or event specifically in the capacity or role of a passenger.
-
C.
isPassengerWith
Indicates that one entity is traveling together with another entity as a passenger in the same vehicle or conveyance.
-
D.
hasPassengerOperations
Indicates that an entity conducts or supports transportation services specifically for carrying passengers.
-
E.
hasPassengerUsageCategory
Indicates the classification of how a passenger-related resource or service is used (e.g., its usage type or category for passengers).
- F. None of above. chosen
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_69f349a80d4481908527317d43f5c579 |
completed | April 30, 2026, 12:23 p.m. |
Created at: May 1, 2026, 1:53 a.m.