Triple
T31187865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hijacking of Air France Flight 139 |
E795098
|
entity |
| Predicate | countryOfOriginOfFlight |
P879
|
FINISHED |
| Object | Israel |
—
|
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: Israel | Statement: [Hijacking of Air France Flight 139, countryOfOriginOfFlight, Israel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfOriginOfFlight Context triple: [Hijacking of Air France Flight 139, countryOfOriginOfFlight, Israel]
-
A.
voyageOriginCountry
chosen
Indicates the country from which a voyage departs or originates.
-
B.
originatingFlight
Indicates that one entity is the original or initial flight from which another flight, journey, or related record derives or is associated.
-
C.
takeoffCountryForRecordFlight
Indicates the country from which a particular record-setting flight departed.
-
D.
aircraftOriginCountry
Indicates the country from which an aircraft originates, such as where it was built, registered, or primarily associated.
-
E.
hasOriginAirport
Indicates that something, typically a flight or journey, departs from or is associated with a specific origin airport.
- 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_69f224d675d08190957198068e440422 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ffc89596d08190b97bd60b45c7f9c0 |
completed | May 9, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69ffc81ba5dc8190ae94d44e2284948f |
completed | May 9, 2026, 11:49 p.m. |
Created at: April 29, 2026, 9:08 p.m.