Triple
T14549449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sauverny |
E341374
|
entity |
| Predicate | hasBorderWith |
P224
|
FINISHED |
| Object | Collex-Bossy |
E10336
|
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: Collex-Bossy | Statement: [Sauverny, hasBorderWith, Collex-Bossy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Collex-Bossy Context triple: [Sauverny, hasBorderWith, Collex-Bossy]
-
A.
Collex-Bossy
chosen
Collex-Bossy is a small municipality in the canton of Geneva in southwestern Switzerland, known for its rural character and proximity to the French border.
-
B.
Lusser
Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
-
C.
Nicollier
Nicollier is the surname of Claude Nicollier, a Swiss astrophysicist and former ESA astronaut known for his Space Shuttle missions and work on the Hubble Space Telescope.
-
D.
Peney-Dessous
Peney-Dessous is a small village in the municipality of Satigny in the canton of Geneva, Switzerland.
-
E.
Balard
Balard is a Paris Métro station in the 15th arrondissement, serving as a key transport hub near the Parc des Expositions and several major administrative and military sites.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2ed2b4c8190945bd26531c71f1f |
completed | April 14, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a6344b08190a3c1124c6dd7da96 |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:23 a.m.