Triple
T7783175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Fribourg |
E187173
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Düdingen
Düdingen is a municipality in western Switzerland known for its bilingual (German-French) character and location near the city of Fribourg.
|
E693431
|
NE FINISHED |
How this triple was built (4 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: Düdingen | Statement: [canton of Fribourg, containsTown, Düdingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Düdingen Context triple: [canton of Fribourg, containsTown, Düdingen]
-
A.
Adliswil
Adliswil is a municipality in the canton of Zurich, Switzerland, situated in the Sihl Valley just south of the city of Zurich.
-
B.
Wädenswil
Wädenswil is a Swiss town in the canton of Zurich known for its lakeside location, wine-growing tradition, and research institutes.
-
C.
Bremgarten
Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
-
D.
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.
-
E.
Arlesheim
Arlesheim is a municipality in the canton of Basel-Landschaft in northwestern Switzerland, known for its historic cathedral and picturesque setting near Basel.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Düdingen Triple: [canton of Fribourg, containsTown, Düdingen]
Generated description
Düdingen is a municipality in western Switzerland known for its bilingual (German-French) character and location near the city of Fribourg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Düdingen Target entity description: Düdingen is a municipality in western Switzerland known for its bilingual (German-French) character and location near the city of Fribourg.
-
A.
Adliswil
Adliswil is a municipality in the canton of Zurich, Switzerland, situated in the Sihl Valley just south of the city of Zurich.
-
B.
Wädenswil
Wädenswil is a Swiss town in the canton of Zurich known for its lakeside location, wine-growing tradition, and research institutes.
-
C.
Bremgarten
Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
-
D.
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.
-
E.
Arlesheim
Arlesheim is a municipality in the canton of Basel-Landschaft in northwestern Switzerland, known for its historic cathedral and picturesque setting near Basel.
- F. None of above. chosen
Provenance (5 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_69ca82af2d2c8190963861f5e0b8bf21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cadf1f9c648190ac2b06d0d54035ea |
completed | March 30, 2026, 8:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69caf5e400d881909d6cdeb7eaac3a59 |
completed | March 30, 2026, 10:15 p.m. |
| NEDg | Description generation | batch_69caf81ebde881909bd131da8987b449 |
completed | March 30, 2026, 10:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cafa013f348190a2067dee4a0c8c40 |
completed | March 30, 2026, 10:32 p.m. |
Created at: March 30, 2026, 4:22 p.m.