Triple
T11133737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Van Nuys Airport |
E263353
|
entity |
| Predicate | hasScheduledCommercialAirlineService |
P70294
|
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: [Van Nuys Airport, hasScheduledCommercialAirlineService, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScheduledCommercialAirlineService Context triple: [Van Nuys Airport, hasScheduledCommercialAirlineService, no]
-
A.
hasNoRegularCommercialAirlineService
chosen
Indicates that a location or facility is not served by any scheduled, routine commercial airline flights.
-
B.
hasPassengerAirlineService
Indicates that a location or facility is served by scheduled passenger airline flights.
-
C.
hasAirlines
Indicates that one entity (such as an airport, city, or country) is served by or associated with one or more airline operators.
-
D.
airlineCommencedOperations
Indicates that an airline began its official flight operations or commercial services on a specific date or at a specific time.
-
E.
servesAirlineType
Indicates that a service provider (such as an airport, terminal, or facility) accommodates or operates flights for a specified type or category of airline.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8347a248190837e8c26f25f553a |
completed | April 9, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69d75ce104908190b6cc31ef2f67846a |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.