Triple
T36005459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SOCATA TB 30 Epsilon |
E1041251
|
entity |
| Predicate | flightTrainingPhase |
P53563
|
FINISHED |
| Object | basic flight training |
—
|
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: basic flight training | Statement: [SOCATA TB 30 Epsilon, flightTrainingPhase, basic flight training]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flightTrainingPhase Context triple: [SOCATA TB 30 Epsilon, flightTrainingPhase, basic flight training]
-
A.
tookFlightTrainingIn
Indicates that an entity received or completed flight training at or through a specified organization, location, or program.
-
B.
trainingWing
Indicates a relationship where one entity serves as a training wing, division, or unit dedicated to instructing or preparing personnel for another entity.
-
C.
flightPhase
chosen
Indicates the specific stage or phase of an aircraft’s operation within a flight (e.g., taxi, takeoff, climb, cruise, descent, landing).
-
D.
hasFlightTrainingActivity
Indicates that an entity is involved in or associated with a flight training activity.
-
E.
hasFixedWingTraining
Indicates that an entity has received training in operating or working with 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_69f76e2a02208190aedd1f9025a8b300 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab75387c819091afc3c2128eb903 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.