Triple
T20484696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S-Bahn Luzern |
E502556
|
entity |
| Predicate | hasPassengerCategory |
P8370
|
FINISHED |
| Object | commuters |
—
|
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: commuters | Statement: [S-Bahn Luzern, hasPassengerCategory, commuters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerCategory Context triple: [S-Bahn Luzern, hasPassengerCategory, commuters]
-
A.
hasPassengerUsageCategory
chosen
Indicates the classification of how a passenger-related resource or service is used (e.g., its usage type or category for passengers).
-
B.
appliesToPassengerType
Indicates that a rule, condition, or attribute is relevant or restricted to a specific type or category of passenger.
-
C.
hasPassengerRole
Indicates that an entity participates in a context or event specifically in the capacity or role of a passenger.
-
D.
passengerCapacityCategory
Indicates the classification of an entity based on the number of passengers it is designed or allowed to carry.
-
E.
hasTicketCategory
Indicates that an item, event, or access right is associated with a specific ticket category or type.
- 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_69e0b4af32848190aea80682b44d5d6e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b59ae2c8190bfa26a3f1e59b8d1 |
completed | April 20, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69e59fcdf6e08190a604204615dc56e6 |
completed | April 20, 2026, 3:38 a.m. |
Created at: April 16, 2026, 11:34 a.m.