Triple
T25854151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LUF |
E651294
|
entity |
| Predicate | publicPassengerService |
P172758
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [LUF, publicPassengerService, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicPassengerService Context triple: [LUF, publicPassengerService, no]
-
A.
formerPassengerService
Indicates that an entity previously provided passenger transportation services but no longer does so.
-
B.
majorPassengerService
Indicates that a transportation facility or route provides primary or significant passenger service as one of its main functions.
-
C.
openedAsPassengerService
Indicates that a transportation facility or route began operating specifically for carrying passengers.
-
D.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
E.
passengerFlight
Indicates a relationship where a flight is specifically operated to transport passengers rather than cargo or other purposes.
- 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_69e7ab39035c8190be15c8aaee1bb858 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6b0d21dd08190a9883ff71c94c71c |
completed | May 3, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
| PDg | Predicate description generation | batch_69f6afeaaef88190aefa97e83f8db906 |
completed | May 3, 2026, 2:16 a.m. |
Created at: April 22, 2026, 7:59 a.m.