Triple
T18340401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gimmelwald |
E439385
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Mürren |
—
|
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: Mürren | Statement: [Gimmelwald, near, Mürren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mürren Context triple: [Gimmelwald, near, Mürren]
-
A.
Mürren
chosen
Mürren is a traditional, car-free mountain village and popular ski resort perched high above the Lauterbrunnen Valley in the Swiss Bernese Alps.
-
B.
Wengen
Wengen is a car-free Swiss alpine village and popular ski and hiking resort located in the Bernese Oberland region.
-
C.
Gimmelwald
Gimmelwald is a small, traditional Swiss alpine village known for its dramatic mountain scenery and tranquil, car-free atmosphere in the Bernese Oberland.
-
D.
Elbigenalp
Elbigenalp is a picturesque village in the Austrian state of Tyrol, known for its alpine scenery and traditional woodcarving craftsmanship.
-
E.
Bürgenstock
Bürgenstock is a Swiss mountain and luxury resort area overlooking Lake Lucerne, known for its panoramic views, historic hotels, and scenic hiking trails.
- 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ed146fc819092b08cb91defb03b |
completed | April 19, 2026, 5:20 p.m. |
Created at: April 10, 2026, 10:37 a.m.