Triple
T1750398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JG 52 |
E38425
|
entity |
| Predicate | approximateAerialVictories |
P10876
|
FINISHED |
| Object | >10000 |
—
|
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: >10000 | Statement: [JG 52, approximateAerialVictories, >10000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateAerialVictories Context triple: [JG 52, approximateAerialVictories, >10000]
-
A.
estimatedAerialVictories
chosen
Indicates an approximate count of aerial combat victories attributed to an entity, rather than an exact, confirmed total.
-
B.
numberOfAerialVictories
Indicates the count of successful aerial combat victories achieved by an entity over opposing aircraft.
-
C.
aircraftAlliedApprox
Indicates that one aircraft is approximately allied with another, reflecting a likely but not definitively confirmed friendly relationship between them.
-
D.
aircraftLosses
Indicates the number or occurrence of aircraft that have been destroyed, damaged beyond repair, or otherwise lost.
-
E.
airSuperiorityContribution
Indicates the extent to which an entity contributes to achieving or maintaining control of the airspace over a given area or conflict.
- 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_69a8862bdb2081908aefe831c8aa8017 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba6a63f588190b53b39c6b97d74f4 |
completed | March 7, 2026, 4:16 a.m. |
| PD | Predicate disambiguation | batch_69aa61c7ef4c8190abec87c96a787d82 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.