Triple
T20114726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tschentenalp |
E490426
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Adelboden |
—
|
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: Adelboden | Statement: [Tschentenalp, locatedIn, Adelboden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adelboden Context triple: [Tschentenalp, locatedIn, Adelboden]
-
A.
Adelboden
chosen
Adelboden is a Swiss alpine village and ski resort in the Bernese Oberland, known for its mountain scenery and World Cup ski races.
-
B.
Wengen
Wengen is a car-free Swiss alpine village and popular ski and hiking resort located in the Bernese Oberland region.
-
C.
Andermatt
Andermatt is a Swiss Alpine village and ski resort in the canton of Uri, known as a major mountain transport hub and tourist destination.
-
D.
Kandersteg
Kandersteg is a Swiss mountain village and popular tourist resort known for its scenic alpine landscapes, hiking trails, and access to Lake Oeschinen.
-
E.
Klosters
Klosters is a renowned Swiss Alpine village and ski resort in the canton of Graubünden, popular for its picturesque scenery and winter sports.
- 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666e3f2288190840d1eb431ac9a1b |
completed | April 20, 2026, 5:48 p.m. |
Created at: April 11, 2026, 11:29 p.m.