Triple
T27546744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ara Zobayan |
E695382
|
entity |
| Predicate | flightDestinationOnAccidentDay |
P87741
|
FINISHED |
| Object | Camarillo Airport, California |
—
|
NE NERFINISHED |
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: Camarillo Airport, California | Statement: [Ara Zobayan, flightDestinationOnAccidentDay, Camarillo Airport, California]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flightDestinationOnAccidentDay Context triple: [Ara Zobayan, flightDestinationOnAccidentDay, Camarillo Airport, California]
-
A.
accidentAirport
Indicates the airport at which an accident involving the subject entity occurred.
-
B.
destinationAirportAtTimeOfCrash
chosen
Indicates the airport that was the intended destination of a flight at the time the crash occurred.
-
C.
destinationAirportInvestigated
Indicates that an airport serving as a destination has been examined or analyzed, typically as part of an investigation or assessment process.
-
D.
destinationAirportOfHijackedFlight
Indicates the airport that served or was intended to serve as the destination of a hijacked flight.
-
E.
intendedDestinationAtAccident
Indicates that a location was the destination an entity was heading toward at the time an accident occurred.
- 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_69ef5386c3e08190bfe33aa326e1f72b |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f6359e3d3c81909814e2f0a7fb0ea9 |
completed | May 2, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f631871c888190bf29466fe4254e51 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 1:33 p.m.