Triple
T15969988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fokker |
E387293
|
entity |
| Predicate | successor |
P78
|
FINISHED |
| Object | Fokker Technologies |
E233655
|
NE 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: Fokker Technologies | Statement: [Fokker, successor, Fokker Technologies]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fokker Technologies Context triple: [Fokker, successor, Fokker Technologies]
-
A.
Fokker Aerostructures
chosen
Fokker Aerostructures is a Dutch aerospace company specializing in the design and manufacture of advanced aircraft structures and components for civil and military programs.
-
B.
Fokker
Fokker is a historic Dutch aerospace company best known for designing and manufacturing civil and military aircraft.
-
C.
Bücker Flugzeugbau
Bücker Flugzeugbau was a German aircraft manufacturer best known for producing light training and sport biplanes in the 1930s and 1940s.
-
D.
Folland Aircraft
Folland Aircraft was a British aircraft manufacturer best known for producing light fighter and trainer aircraft in the post-World War II era.
-
E.
Pilatus Aircraft
Pilatus Aircraft is a Swiss aerospace manufacturer best known for producing high-performance turboprop training and utility aircraft for military and civilian use.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157291214819088d65e984609e42c |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe88fa308190942d37cf67458396 |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:54 a.m.