Triple
T8407890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spirit of St. Louis Airport |
E198544
|
entity |
| Predicate | hasFlightTraining |
P60836
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Spirit of St. Louis Airport, hasFlightTraining, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlightTraining Context triple: [Spirit of St. Louis Airport, hasFlightTraining, yes]
-
A.
hasFlightTrainingActivity
chosen
Indicates that an entity is involved in or associated with a flight training activity.
-
B.
hasFixedWingTrainingRole
Indicates that an entity serves in a training capacity specifically related to the operation or use of fixed-wing aircraft.
-
C.
hasHelicopterTrainingRole
Indicates that an entity holds a role or position specifically related to the training or instruction of helicopter operations.
-
D.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
E.
airborneQualified
Indicates that an entity has successfully completed airborne training and is certified or qualified to conduct airborne (parachute) operations.
- 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_69ca8310df9c8190b25f16161cca3e41 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb8315a8a8819097f6da11b909b527 |
completed | March 31, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69cb70d473dc8190af8ea81ee5aa970d |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:05 p.m.