Triple
T36914312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MDANG |
E913002
|
entity |
| Predicate | hasFlyingUnit |
P186678
|
FINISHED |
| Object | 104th Fighter Squadron |
—
|
NE NERFINISHED |
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: 104th Fighter Squadron | Statement: [MDANG, hasFlyingUnit, 104th Fighter Squadron]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlyingUnit Context triple: [MDANG, hasFlyingUnit, 104th Fighter Squadron]
-
A.
aerialUnit
Indicates that the related entity functions as or is classified as an aerial unit, typically operating or acting in the air rather than on the ground or sea.
-
B.
isHelicopterOf
Indicates that one entity is a helicopter that belongs to, is operated by, or is otherwise associated with another entity.
-
C.
isMilitaryAircraft
Indicates that the subject aircraft is designed, used, or designated for military purposes rather than civilian use.
-
D.
usesAircraftFeature
Indicates that one entity employs or takes advantage of a specific feature or capability of an aircraft.
-
E.
hasAerial
Indicates that an entity is equipped with or possesses an aerial or antenna component.
- 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_69f76e879768819085c2fb31a6a5b44b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf79ddb08190a083405cccc14137 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:13 p.m.