Triple
T20264647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hans-Joachim Marseille |
E498931
|
entity |
| Predicate | numberOfSortiesFlown |
P115871
|
FINISHED |
| Object | over 380 |
—
|
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 380 | Statement: [Hans-Joachim Marseille, numberOfSortiesFlown, over 380]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSortiesFlown Context triple: [Hans-Joachim Marseille, numberOfSortiesFlown, over 380]
-
A.
hasFlownSorties
Indicates that an entity has completed one or more operational flight missions (sorties).
-
B.
dailySorties
Indicates the number of missions or operations carried out per day by an entity.
-
C.
approximateSorties
chosen
Indicates an estimated or rough count of sorties (missions or flights) rather than an exact, precise number.
-
D.
numberOfSuccessfulMissions
Indicates the count of missions that have been completed successfully by the referenced entity or within the specified context.
-
E.
numberOfAerialVictories
Indicates the count of successful aerial combat victories achieved by an entity over opposing aircraft.
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e674ce27688190b31d7a6c98d3ec5e |
completed | April 20, 2026, 6:47 p.m. |
| PD | Predicate disambiguation | batch_69e55b1e5e1c8190ba8a5544b1db9e1d |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:41 p.m.