Triple
T7911411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air Force Outstanding Unit Award |
E183706
|
entity |
| Predicate | fiveAwardsIndicatedBy |
P23624
|
FINISHED |
| Object | silver oak leaf cluster |
—
|
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: silver oak leaf cluster | Statement: [Air Force Outstanding Unit Award, fiveAwardsIndicatedBy, silver oak leaf cluster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fiveAwardsIndicatedBy Context triple: [Air Force Outstanding Unit Award, fiveAwardsIndicatedBy, silver oak leaf cluster]
-
A.
numberOfAwards
Indicates the total count of awards that have been received by an entity.
-
B.
hasMultipleAwardsIndicatedBy
chosen
Indicates that an entity is recognized as having received multiple awards, as evidenced or signaled by a specified source or indicator.
-
C.
mostAwardsFilm
Indicates that a film is the one that has received the highest number of awards within a given set or context.
-
D.
academyAwardsNominationsCount
Indicates the number of times an entity has been nominated for an Academy Award.
-
E.
academyAwardWins
Indicates that one entity has won a specified number of Academy Awards (Oscars) or that a winning relationship exists between the entity and the Academy Award.
- 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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a725b8c8190a530adb3107a95dd |
completed | March 31, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69cae92f9498819085277879e59aa072 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:04 p.m.