Triple
T2445441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernex |
E53379
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object | Onex |
E29604
|
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: Onex | Statement: [Bernex, hasNeighboringMunicipality, Onex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Onex Context triple: [Bernex, hasNeighboringMunicipality, Onex]
-
A.
Onex
chosen
Onex is a suburban municipality in western Switzerland located just outside the city of Geneva.
-
B.
Ornex
Ornex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
-
C.
Setonix
Setonix is a genus of small marsupials best known for including the quokka, a short-tailed wallaby native to southwestern Australia.
-
D.
Zyvex
Zyvex is a pioneering nanotechnology company known for its early work in molecular nanotechnology and advanced manufacturing.
-
E.
Unternehmen Merkur
Unternehmen Merkur was the German airborne and seaborne invasion operation that led to the capture of Crete from Allied forces in May 1941 during World War II.
- 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_69aef0baa6448190a4046a039168b8fe |
completed | March 9, 2026, 4:09 p.m. |
Created at: March 6, 2026, 9:43 p.m.