Triple
T10413903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LOT Miles & More Senator |
E245464
|
entity |
| Predicate | allowsGuestAccessToLounge |
P32331
|
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: [LOT Miles & More Senator, allowsGuestAccessToLounge, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allowsGuestAccessToLounge Context triple: [LOT Miles & More Senator, allowsGuestAccessToLounge, yes]
-
A.
hasCustomerLounge
Indicates that an entity provides or includes a designated lounge area for customers to use.
-
B.
hasPassengerCheckInAccess
Indicates that an entity is permitted to perform or access passenger check-in functions for a given transport service or location.
-
C.
airportAccessMode
Indicates the typical mode or method of transportation used to access or reach an airport.
-
D.
hasLoungeType
Indicates that an entity is associated with, or classified by, a particular type or category of lounge.
-
E.
passengerAccess
chosen
Indicates that a passenger is allowed to enter, use, or move through a particular vehicle, area, or transportation-related facility.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea0ec6fc8190a71af759226a3cba |
completed | April 7, 2026, 11:27 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb6f160819090040644a12395ec |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:10 p.m.