Triple
T23803911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 102nd Fighter Wing |
E589648
|
entity |
| Predicate | historicalAircraftRole |
P153618
|
FINISHED |
| Object | fighter aircraft |
—
|
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: fighter aircraft | Statement: [102nd Fighter Wing, historicalAircraftRole, fighter aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalAircraftRole Context triple: [102nd Fighter Wing, historicalAircraftRole, fighter aircraft]
-
A.
notableAircraftRole
Indicates that an aircraft is notably associated with performing a particular role or function.
-
B.
historicalAircraftOperated
Indicates that an entity previously operated a specific aircraft model during a past period, but no longer does so.
-
C.
notableAircraftTheater
Indicates that an aircraft is notably associated with operations or service in a particular theater of activity or conflict.
-
D.
aircraftRoleDesigned
Indicates that an aircraft was specifically designed to fulfill a particular operational role or function.
-
E.
aircraftRoleOperated
Indicates that an entity operates or has operated in a specified role or function within the context of aircraft 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_69e25d19fecc8190a5cf39bbb18d5d7f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c750048c8190899ff611df35b361 |
completed | April 29, 2026, 8:54 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
| PDg | Predicate description generation | batch_69f15adb23d88190ac2632299c26a9b3 |
completed | April 29, 2026, 1:11 a.m. |
Created at: April 17, 2026, 7:55 p.m.