Triple
T17591366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interlaken–Lucerne route |
E428454
|
entity |
| Predicate | hasViewOf |
P854
|
FINISHED |
| Object | Pilatus |
—
|
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 | Statement: [Interlaken–Lucerne route, hasViewOf, Pilatus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pilatus Context triple: [Interlaken–Lucerne route, hasViewOf, Pilatus]
-
A.
Pilatus
chosen
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.
-
B.
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.
-
C.
Fairchild-Dornier
Fairchild-Dornier was a German-American aircraft manufacturer formed in the 1990s that focused on regional and business jets before declaring bankruptcy in the early 2000s.
-
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.
Schleicher
Schleicher is a German surname borne by various notable figures in fields such as politics, linguistics, and education.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e469e6e3888190b73a5b6d7e8c0a55 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 5:51 a.m.