Triple
T10189568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Musée des Beaux-Arts de Chambéry |
E237996
|
entity |
| Predicate | operatedBy |
P86
|
FINISHED |
| Object | City of Chambéry |
E46643
|
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: City of Chambéry | Statement: [Musée des Beaux-Arts de Chambéry, operatedBy, City of Chambéry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Chambéry Context triple: [Musée des Beaux-Arts de Chambéry, operatedBy, City of Chambéry]
-
A.
Chambéry
chosen
Chambéry is a historic city in southeastern France that served as the political and cultural center of the former Duchy of Savoy.
-
B.
Champéry
Champéry is a Swiss alpine village and ski resort in the canton of Valais, known for its access to the Portes du Soleil ski area and mountain tourism.
-
C.
Lancy
Lancy is a suburban municipality in western Switzerland that forms part of the urban area of Geneva.
-
D.
Embrun
Embrun is a historic town in southeastern France’s Hautes-Alpes department, known for its picturesque setting in the Alps and proximity to the Lac de Serre-Ponçon.
-
E.
Embrun
Embrun is a rapidly growing Franco-Ontarian community in eastern Ontario, known for its bilingual character and proximity to Ottawa.
- 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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded7d6fdc81908052866495b6574f |
completed | April 2, 2026, 4:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7947e14c88190b9e33e3fbdcc16e5 |
completed | April 9, 2026, 11:58 a.m. |
Created at: March 30, 2026, 9:12 p.m.