Triple
T8091728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernese Oberland |
E188881
|
entity |
| Predicate | hasMajorResort |
P10436
|
FINISHED |
| Object | Kandersteg |
E105048
|
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: Kandersteg | Statement: [Bernese Oberland, hasMajorResort, Kandersteg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kandersteg Context triple: [Bernese Oberland, hasMajorResort, Kandersteg]
-
A.
Kandersteg
chosen
Kandersteg is a Swiss mountain village and popular tourist resort known for its scenic alpine landscapes, hiking trails, and access to Lake Oeschinen.
-
B.
Wengen
Wengen is a car-free Swiss alpine village and popular ski and hiking resort located in the Bernese Oberland region.
-
C.
Visp
Visp is a small town in the canton of Valais in southwestern Switzerland, situated in the Rhône valley and known as a regional transport hub and gateway to nearby Alpine resorts.
-
D.
Klosters
Klosters is a renowned Swiss Alpine village and ski resort in the canton of Graubünden, popular for its picturesque scenery and winter sports.
-
E.
Weggis
Weggis is a picturesque lakeside resort town in central Switzerland, known for its mild climate, scenic views of the Alps, and tourism on the shores of Lake Lucerne.
- 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_69ca82b7b3e88190b9041ab0ef28b3cb |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42217a1881909792b08a2f06fb75 |
completed | March 31, 2026, 3:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce88498cf081909c25c292c014fe8c |
completed | April 2, 2026, 3:16 p.m. |
Created at: March 30, 2026, 5:30 p.m.