Triple
T2222662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hermann Graf |
E48175
|
entity |
| Predicate | serviceNumberOfAerialVictories |
P12250
|
FINISHED |
| Object | over 200 |
—
|
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: over 200 | Statement: [Hermann Graf, serviceNumberOfAerialVictories, over 200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceNumberOfAerialVictories Context triple: [Hermann Graf, serviceNumberOfAerialVictories, over 200]
-
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.
aircraftFlown
Indicates that an entity (typically a person or organization) operates or pilots a particular aircraft.
-
D.
airSuperiorityContribution
Indicates the extent to which an entity contributes to achieving or maintaining control of the airspace over a given area or conflict.
-
E.
aircraftLosses
Indicates the number or occurrence of aircraft that have been destroyed, damaged beyond repair, or otherwise lost.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc03bfdd48190bfb96ec3e41c22dc |
completed | March 7, 2026, 6:05 a.m. |
| PD | Predicate disambiguation | batch_69abbdac31d8819092d17815e11921e9 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.