Triple
T33652743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SU-GAP |
E862140
|
entity |
| Predicate | destinationAirportOnAccidentFlight |
P87741
|
FINISHED |
| Object | Cairo International Airport |
—
|
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: Cairo International Airport | Statement: [SU-GAP, destinationAirportOnAccidentFlight, Cairo International Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: destinationAirportOnAccidentFlight Context triple: [SU-GAP, destinationAirportOnAccidentFlight, Cairo International Airport]
-
A.
destinationAirportOfHijackedFlight
Indicates the airport that served or was intended to serve as the destination of a hijacked flight.
-
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.
destinationAirportICAO
Indicates the airport, identified by its ICAO code, that serves as the destination in a flight or travel-related context.
-
E.
destinationAirportName
Indicates the name of the airport that serves as the destination in a travel or flight-related relationship.
- 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_69f349840ba881908e3bfce536aeb92b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:42 a.m.