Triple
T641067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haute-Savoie |
E16739
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Cluses
Cluses is a small industrial town in southeastern France known for its precision engineering and watchmaking heritage, located in the Arve Valley of the Haute-Savoie department in the Alps.
|
E112902
|
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: Cluses | Statement: [Haute-Savoie, containsCity, Cluses]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cluses Context triple: [Haute-Savoie, containsCity, Cluses]
-
A.
Bardonnex
Bardonnex is a small Swiss municipality located in the canton of Geneva, near the country’s border with France.
-
B.
Corsier-sur-Vevey
Corsier-sur-Vevey is a small municipality on the shores of Lake Geneva in the canton of Vaud, Switzerland, known as the final home of film legend Charlie Chaplin.
-
C.
Aubonne
Aubonne is a river in western Switzerland that flows through the canton of Vaud before emptying into Lake Geneva.
-
D.
Lancy
Lancy is a suburban municipality in western Switzerland that forms part of the urban area of Geneva.
-
E.
Chêne-Bougeries
Chêne-Bougeries is a suburban municipality in western Switzerland, located just east of the city of Geneva in the canton of Geneva.
- 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: Cluses Triple: [Haute-Savoie, containsCity, Cluses]
Generated description
Cluses is a small industrial town in southeastern France known for its precision engineering and watchmaking heritage, located in the Arve Valley of the Haute-Savoie department in the Alps.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cluses Target entity description: Cluses is a small industrial town in southeastern France known for its precision engineering and watchmaking heritage, located in the Arve Valley of the Haute-Savoie department in the Alps.
-
A.
Bardonnex
Bardonnex is a small Swiss municipality located in the canton of Geneva, near the country’s border with France.
-
B.
Corsier-sur-Vevey
Corsier-sur-Vevey is a small municipality on the shores of Lake Geneva in the canton of Vaud, Switzerland, known as the final home of film legend Charlie Chaplin.
-
C.
Aubonne
Aubonne is a river in western Switzerland that flows through the canton of Vaud before emptying into Lake Geneva.
-
D.
Lancy
Lancy is a suburban municipality in western Switzerland that forms part of the urban area of Geneva.
-
E.
Chêne-Bougeries
Chêne-Bougeries is a suburban municipality in western Switzerland, located just east of the city of Geneva in the canton of Geneva.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49f0189b08190a584b744f36fa761 |
completed | March 1, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac1185da8c8190a70f4fd885bbe209 |
completed | March 7, 2026, 11:52 a.m. |
| NEDg | Description generation | batch_69ac1279e9d481908644b2e6c6bdb645 |
completed | March 7, 2026, 11:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac12fba71881909537bc73c8f6c620 |
completed | March 7, 2026, 11:58 a.m. |
Created at: March 1, 2026, 7:36 p.m.