Triple
T36576631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hani Hanjour |
E902272
|
entity |
| Predicate | tookFlightTrainingAt |
P87281
|
FINISHED |
| Object | Arizona flight schools |
—
|
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: Arizona flight schools | Statement: [Hani Hanjour, tookFlightTrainingAt, Arizona flight schools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tookFlightTrainingAt Context triple: [Hani Hanjour, tookFlightTrainingAt, Arizona flight schools]
-
A.
tookFlightTrainingIn
chosen
Indicates that an entity received or completed flight training at or through a specified organization, location, or program.
-
B.
hasFlightTrainingActivity
Indicates that an entity is involved in or associated with a flight training activity.
-
C.
hasFlightTrainingFacility
Indicates that an entity provides or hosts a facility where flight training or pilot instruction is conducted.
-
D.
hasFixedWingTraining
Indicates that an entity has received training in operating or working with fixed-wing aircraft.
-
E.
hasFixedWingTrainingRole
Indicates that an entity serves in a training capacity specifically related to the operation or use of fixed-wing aircraft.
- 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_69f76e64d8908190868473959a250b94 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1baf25c8190a78dd54a400d2c50 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:11 p.m.