Triple
T14250947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Thurgau |
E353258
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Weinfelden |
E998117
|
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: Weinfelden | Statement: [canton of Thurgau, hasCity, Weinfelden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weinfelden Context triple: [canton of Thurgau, hasCity, Weinfelden]
-
A.
Weinfelden
chosen
Weinfelden is a town and municipality in northeastern Switzerland that serves as an important regional center in the canton of Thurgau.
-
B.
Reigoldswil
Reigoldswil is a municipality in the canton of Basel-Landschaft in northwestern Switzerland, known as a gateway to the Jura hills and local hiking areas.
-
C.
Walperswil
Walperswil is a small municipality in the canton of Bern in Switzerland.
-
D.
Wädenswil
Wädenswil is a Swiss town in the canton of Zurich known for its lakeside location, wine-growing tradition, and research institutes.
-
E.
Andelfingen
Andelfingen is a municipality and regional center in the canton of Zürich in northern Switzerland, known for its rural character and vineyards along the Thur River.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6296f9d0819086f62f525d07eb12 |
completed | April 14, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda904f8ac8190a4206b6ab6ee812c |
completed | May 8, 2026, 9:12 a.m. |
Created at: April 10, 2026, 1:08 a.m.