Triple
T747729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernese Alps |
E15379
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Adelboden
Adelboden is a Swiss alpine village and ski resort in the Bernese Oberland, known for its mountain scenery and World Cup ski races.
|
E106528
|
NE FINISHED |
How this triple was built (4 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: [Bernese Alps, contains, Adelboden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adelboden Context triple: [Bernese Alps, contains, Adelboden]
-
A.
Wengen
Wengen is a car-free Swiss alpine village and popular ski and hiking resort located in the Bernese Oberland region.
-
B.
Kandersteg
Kandersteg is a Swiss mountain village and popular tourist resort known for its scenic alpine landscapes, hiking trails, and access to Lake Oeschinen.
-
C.
Mürren
Mürren is a traditional, car-free mountain village and popular ski resort perched high above the Lauterbrunnen Valley in the Swiss Bernese Alps.
-
D.
Saas-Fee
Saas-Fee is a high-altitude Swiss alpine village and ski resort in the Valais Alps, known for its car-free center, extensive glacier skiing, and dramatic mountain scenery.
-
E.
Zermatt
Zermatt is a renowned Swiss alpine resort village in the canton of Valais, famous for its skiing, mountaineering, and proximity to iconic peaks like the Matterhorn.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Adelboden Triple: [Bernese Alps, contains, Adelboden]
Generated description
Adelboden is a Swiss alpine village and ski resort in the Bernese Oberland, known for its mountain scenery and World Cup ski races.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Adelboden Target entity description: Adelboden is a Swiss alpine village and ski resort in the Bernese Oberland, known for its mountain scenery and World Cup ski races.
-
A.
Wengen
Wengen is a car-free Swiss alpine village and popular ski and hiking resort located in the Bernese Oberland region.
-
B.
Kandersteg
Kandersteg is a Swiss mountain village and popular tourist resort known for its scenic alpine landscapes, hiking trails, and access to Lake Oeschinen.
-
C.
Mürren
Mürren is a traditional, car-free mountain village and popular ski resort perched high above the Lauterbrunnen Valley in the Swiss Bernese Alps.
-
D.
Saas-Fee
Saas-Fee is a high-altitude Swiss alpine village and ski resort in the Valais Alps, known for its car-free center, extensive glacier skiing, and dramatic mountain scenery.
-
E.
Zermatt
Zermatt is a renowned Swiss alpine resort village in the canton of Valais, famous for its skiing, mountaineering, and proximity to iconic peaks like the Matterhorn.
- F. None of above. chosen
Provenance (5 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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a62dd1bc819094a3814654448ae3 |
completed | March 1, 2026, 8:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c70c30d48190838ebe5db89d0b7a |
completed | March 4, 2026, 5:45 a.m. |
| NEDg | Description generation | batch_69a7c82c5b888190ae5440f5d06d2bce |
completed | March 4, 2026, 5:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7c8991e7c81908c31d60f9a7f2340 |
completed | March 4, 2026, 5:52 a.m. |
Created at: March 1, 2026, 7:37 p.m.