Triple
T2445442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernex |
E53379
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object | Confignon |
E174462
|
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: Confignon | Statement: [Bernex, hasNeighboringMunicipality, Confignon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Confignon Context triple: [Bernex, hasNeighboringMunicipality, Confignon]
-
A.
Confignon
chosen
Confignon is a small municipality in the canton of Geneva in southwestern Switzerland, known for its residential character and proximity to the city of Geneva.
-
B.
Sauvy
Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
-
C.
Cigales
Cigales is a small town in the province of Valladolid, Spain, known historically as a royal residence and for its wine production.
-
D.
Aligoté
Aligoté is a white grape variety from Burgundy known for producing light, crisp, and high-acid wines often enjoyed young.
-
E.
Montmorency
Montmorency is a commune in the northern suburbs of Paris, France, known for its historic town center and surrounding Val-d'Oise area.
- 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_69ab495b6dac8190ac82661aa1452222 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abca23ebe8819099a579a07c1bb708 |
completed | March 7, 2026, 6:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af9060a6b88190b80e5fb0970957e1 |
completed | March 10, 2026, 3:30 a.m. |
Created at: March 6, 2026, 9:43 p.m.