Triple
T23282953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stans |
E588915
|
entity |
| Predicate | hasCompany |
P1287
|
FINISHED |
| Object | Pilatus Aircraft |
—
|
NE NERFINISHED |
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: Pilatus Aircraft | Statement: [Stans, hasCompany, Pilatus Aircraft]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pilatus Aircraft Context triple: [Stans, hasCompany, Pilatus Aircraft]
-
A.
Pilatus Aircraft
chosen
Pilatus Aircraft is a Swiss aerospace manufacturer best known for producing high-performance turboprop training and utility aircraft for military and civilian use.
-
B.
Pilatus
Pilatus is a prominent mountain massif overlooking Lucerne in central Switzerland, famed for its panoramic views, hiking trails, and the world’s steepest cogwheel railway.
-
C.
Schweizer Aircraft
Schweizer Aircraft was an American aerospace manufacturer known for producing light helicopters, sailplanes, and small aircraft, including later versions of the Hughes 300 helicopter.
-
D.
Bücker Flugzeugbau
Bücker Flugzeugbau was a German aircraft manufacturer best known for producing light training and sport biplanes in the 1930s and 1940s.
-
E.
Nord Aviation
Nord Aviation was a French aerospace manufacturer known for producing military and civil aircraft and later becoming part of Aérospatiale.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196447a748190bd797ec9baa63fc3 |
completed | April 29, 2026, 5:25 a.m. |
Created at: April 17, 2026, 4:58 p.m.