Triple
T6749814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Scherrer Institute |
E154314
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Villigen
Villigen is a municipality in the canton of Aargau, Switzerland, known for hosting major scientific research facilities.
|
E615847
|
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: Villigen | Statement: [Paul Scherrer Institute, locatedIn, Villigen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Villigen Context triple: [Paul Scherrer Institute, locatedIn, Villigen]
-
A.
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.
-
B.
Bönigen
Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
-
C.
Volketswil
Volketswil is a municipality in the canton of Zurich in Switzerland, known for its residential character and proximity to the city of Zurich.
-
D.
Aarburg
Aarburg is a historic Swiss town in the canton of Aargau, known for its prominent riverside fortress overlooking the Aare River.
-
E.
Attiswil
Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
- 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: Villigen Triple: [Paul Scherrer Institute, locatedIn, Villigen]
Generated description
Villigen is a municipality in the canton of Aargau, Switzerland, known for hosting major scientific research facilities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Villigen Target entity description: Villigen is a municipality in the canton of Aargau, Switzerland, known for hosting major scientific research facilities.
-
A.
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.
-
B.
Bönigen
Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
-
C.
Volketswil
Volketswil is a municipality in the canton of Zurich in Switzerland, known for its residential character and proximity to the city of Zurich.
-
D.
Aarburg
Aarburg is a historic Swiss town in the canton of Aargau, known for its prominent riverside fortress overlooking the Aare River.
-
E.
Attiswil
Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
- 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_69c6880ef37881909268a5a7299b9293 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1da32108190882949aa329d2b60 |
completed | March 27, 2026, 6:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70b180f188190b380909c46fbce40 |
completed | March 27, 2026, 10:56 p.m. |
| NEDg | Description generation | batch_69c70c334a90819084bb0b25bbc112cc |
completed | March 27, 2026, 11:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c70d0fcbc08190b3a7d0de3c634a5f |
completed | March 27, 2026, 11:04 p.m. |
Created at: March 27, 2026, 2:11 p.m.