Triple
T19481421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matten bei Interlaken |
E487392
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object | Bönigen |
E444864
|
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: Bönigen | Statement: [Matten bei Interlaken, hasNeighboringMunicipality, Bönigen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bönigen Context triple: [Matten bei Interlaken, hasNeighboringMunicipality, Bönigen]
-
A.
Bönigen
chosen
Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
-
B.
Bremgarten
Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
-
C.
Villigen
Villigen is a municipality in the canton of Aargau, Switzerland, known for hosting major scientific research facilities.
-
D.
Bäriswil
Bäriswil is a small municipality in the canton of Bern in Switzerland, known for its rural character and proximity to the city of Bern.
-
E.
Kesswil
Kesswil is a small Swiss village on the shores of Lake Constance, best known as the birthplace of the influential psychiatrist and psychoanalyst Carl Gustav Jung.
- 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e634393b8081909f5e4c38b2f1a9b7 |
completed | April 20, 2026, 2:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07c4e296e0819094b49185e64e5da0 |
completed | May 16, 2026, 1:14 a.m. |
Created at: April 10, 2026, 1:39 p.m.