Triple
T9014329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LAX Shuttle G (historical designation) |
E215553
|
entity |
| Predicate | servedPassengers |
P71580
|
FINISHED |
| Object | airline 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: airline passengers | Statement: [LAX Shuttle G (historical designation), servedPassengers, airline passengers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedPassengers Context triple: [LAX Shuttle G (historical designation), servedPassengers, airline passengers]
-
A.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
B.
passengerCount
Indicates the number of passengers associated with a given entity, such as a vehicle or trip.
-
C.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
D.
hasPassengerAirlineService
chosen
Indicates that a location or facility is served by scheduled passenger airline flights.
-
E.
passengersCountApproximate
Indicates that the number of passengers involved is given as an approximate or estimated count rather than an exact figure.
- 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_69ca83a2bf088190986ee7a8eb90407d |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69fae0b88190a0aa989bc37ab2c7 |
completed | April 1, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69cc5edf84408190aa5f57cb8bfd00e1 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:06 p.m.