Triple
T27546740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ara Zobayan |
E695382
|
entity |
| Predicate | numberOfPeopleOnBoardAccidentFlight |
P35405
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Ara Zobayan, numberOfPeopleOnBoardAccidentFlight, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPeopleOnBoardAccidentFlight Context triple: [Ara Zobayan, numberOfPeopleOnBoardAccidentFlight, 9]
-
A.
totalPeopleOnBoard
chosen
Indicates the total number of people currently present on a given vehicle, vessel, or similar conveyance.
-
B.
fatalitiesOnboard
Indicates that the relationship specifies the number of people who died among those present on a particular vehicle or craft.
-
C.
flightNumberInAccident
Indicates that a specific flight number is associated with an accident event.
-
D.
passengersAtTimeOfDestruction
Indicates that the specified passengers were present on or associated with the entity (e.g., a vehicle or vessel) at the moment it was destroyed.
-
E.
honorsNumberOfPassengersAndCrew
Indicates that the subject recognizes or commemorates the specified count of passengers and crew.
- 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_69fee691952c8190822da83e46311d1d |
completed | May 9, 2026, 7:47 a.m. |
| PD | Predicate disambiguation | batch_69fee62f285c8190a625562a9b80526e |
completed | May 9, 2026, 7:45 a.m. |
Created at: April 27, 2026, 1:33 p.m.