Triple
T7116895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XVIII Airborne Corps |
E165841
|
entity |
| Predicate | airborneQualified |
P74646
|
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: [XVIII Airborne Corps, airborneQualified, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airborneQualified Context triple: [XVIII Airborne Corps, airborneQualified, yes]
-
A.
hasFixedWingTrainingRole
Indicates that an entity serves in a training capacity specifically related to the operation or use of fixed-wing aircraft.
-
B.
aircraftCommanded
Indicates that one entity serves as the commanding officer or leader in charge of operating, directing, or overseeing the other entity, which is an aircraft.
-
C.
aircraftRoleRequired
Indicates that a specific operational role or function is required of an aircraft within a given context or mission.
-
D.
aircraftFlown
Indicates that an entity (typically a person or organization) operates or pilots a particular aircraft.
-
E.
hasHelicopterTrainingRole
Indicates that an entity holds a role or position specifically related to the training or instruction of helicopter operations.
- F. None of above. chosen
Provenance (4 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e617a528819085d4b8e1b5699966 |
completed | March 27, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c4f9788190830288d00cc37026 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e456e89481908df42a1b4232a4a0 |
completed | March 27, 2026, 8:11 p.m. |
Created at: March 27, 2026, 2:43 p.m.