Triple
T17674004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FRA |
E440597
|
entity |
| Predicate | hasPassengerLounges |
P13530
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [FRA, hasPassengerLounges, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerLounges Context triple: [FRA, hasPassengerLounges, Yes]
-
A.
hasCustomerLounge
chosen
Indicates that an entity provides or includes a designated lounge area for customers to use.
-
B.
hasPassengerAmenity
Indicates that an entity provides or is equipped with a specific amenity intended for the comfort or convenience of its passengers.
-
C.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
D.
hasPassengerCheckInAccess
Indicates that an entity is permitted to perform or access passenger check-in functions for a given transport service or location.
-
E.
hasPassengerAirlineService
Indicates that a location or facility is served by scheduled passenger airline flights.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f6ba22081909e2099490c047378 |
completed | April 19, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69e3cde007d8819090dd92eea9f022cc |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 10 a.m.