Triple
T19800155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beinwil am See |
E475650
|
entity |
| Predicate | neighboringMunicipality |
P17964
|
FINISHED |
| Object | Menziken |
—
|
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: Menziken | Statement: [Beinwil am See, neighboringMunicipality, Menziken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Menziken Context triple: [Beinwil am See, neighboringMunicipality, Menziken]
-
A.
Menziken
chosen
Menziken is a municipality in the canton of Aargau in Switzerland, known historically for its metalworking and manufacturing industries.
-
B.
Menzeys
Menzeys is an alternative spelling of the surname Menzies, which is of Scottish origin.
-
C.
Horki
Horki is a town in eastern Belarus known for its agricultural academy and regional administrative significance.
-
D.
Kogarah
Kogarah is a suburb in southern Sydney, New South Wales, Australia, known as a residential and commercial hub in the St George area.
-
E.
Mosen
Mosen is a small Swiss village in the canton of Lucerne, situated in a rural lakeside setting in central Switzerland.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653cb865c81909696d2b37476f62f |
completed | April 20, 2026, 4:26 p.m. |
Created at: April 10, 2026, 1:49 p.m.