Triple
T13402913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brugg District |
E319876
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Villigen |
E615847
|
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: Villigen | Statement: [Brugg District, hasMunicipality, Villigen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Villigen Context triple: [Brugg District, hasMunicipality, Villigen]
-
A.
Villigen
chosen
Villigen is a municipality in the canton of Aargau, Switzerland, known for hosting major scientific research facilities.
-
B.
Walchwil
Walchwil is a picturesque Swiss municipality in the canton of Zug, known for its scenic location on the eastern shore of Lake Zug and views of the surrounding Alps.
-
C.
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.
-
D.
Bönigen
Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
-
E.
Uttwil
Uttwil is a small Swiss municipality on the southern shore of Lake Constance in the canton of Thurgau.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbae4982e0819087a9fcb2fa88541f |
completed | April 12, 2026, 2:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d360c60819086a8168bdc092e1c |
completed | May 3, 2026, 7:08 p.m. |
Created at: April 9, 2026, 9:34 p.m.