Triple
T20025064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zone 12 |
E494957
|
entity |
| Predicate | appliesToPassengerType |
P138413
|
FINISHED |
| Object | adult passengers |
—
|
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: adult passengers | Statement: [Zone 12, appliesToPassengerType, adult passengers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToPassengerType Context triple: [Zone 12, appliesToPassengerType, adult passengers]
-
A.
hasPassengerUsageCategory
Indicates the classification of how a passenger-related resource or service is used (e.g., its usage type or category for passengers).
-
B.
isPassengerOnly
Indicates that the subject entity is restricted to passenger use only and does not accommodate cargo, freight, or mixed-use purposes.
-
C.
appliesToTransportMode
Indicates that a rule, condition, or characteristic is specifically associated with and relevant to a particular mode of transport.
-
D.
appliedToVehicleType
Indicates that something (such as a rule, restriction, or condition) is specifically applicable to a particular type or category of vehicle.
-
E.
hasPassengerOnlyService
Indicates that the service provided involves only the transportation of passengers, with no freight or cargo component.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6628b6b7c81909a660fbec9c92295 |
completed | April 20, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:35 p.m.