Triple
T4428298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edward O'Hare |
E95261
|
entity |
| Predicate | numberOfEnemyAircraftShotDownInNotableAction |
P12250
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Edward O'Hare, numberOfEnemyAircraftShotDownInNotableAction, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfEnemyAircraftShotDownInNotableAction Context triple: [Edward O'Hare, numberOfEnemyAircraftShotDownInNotableAction, 5]
-
A.
numberOfAerialVictories
chosen
Indicates the count of successful aerial combat victories achieved by an entity over opposing aircraft.
-
B.
estimatedAerialVictories
Indicates an approximate count of aerial combat victories attributed to an entity, rather than an exact, confirmed total.
-
C.
notableAirOperation
Indicates that there is a significant or historically important air operation associated with the subject.
-
D.
aircraftFlown
Indicates that an entity (typically a person or organization) operates or pilots a particular aircraft.
-
E.
typeOfAerialVictories
Indicates the specific category or classification of aerial victories associated with an entity.
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355674d5481908bf2dfd611f3520f |
completed | March 13, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69b34f5eabe88190a12b244ea71e46d6 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:30 p.m.