Triple
T12949936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramstein airshow disaster |
E309865
|
entity |
| Predicate | involvedAircraftNumber |
P5710
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Ramstein airshow disaster, involvedAircraftNumber, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvedAircraftNumber Context triple: [Ramstein airshow disaster, involvedAircraftNumber, 3]
-
A.
numberOfPlanes
chosen
Indicates the quantity of planes associated with or involved in a given entity or situation.
-
B.
referredAircraftUsedIn
Indicates that an aircraft being referred to is the one that was actually used in a particular event, operation, or context.
-
C.
referredAircraftUsedFor
Indicates that the referenced aircraft is utilized for a particular purpose, role, or operation in relation to another entity or context.
-
D.
intendedAircraft
Indicates that an aircraft is the one planned or designated to be used for a particular flight, mission, or operation.
-
E.
fuselageCount
Indicates the number of fuselages associated with or contained in an aircraft or aerospace structure.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:43 p.m.