Triple
T230912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Geneva |
E4408
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Meyrin |
E47537
|
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: Meyrin | Statement: [canton of Geneva, hasMunicipality, Meyrin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meyrin Context triple: [canton of Geneva, hasMunicipality, Meyrin]
-
A.
Meyrin
chosen
Meyrin is a municipality in the canton of Geneva, Switzerland, best known for hosting major CERN facilities including the Super Proton Synchrotron.
-
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.
Chamonix
Chamonix is a renowned French alpine town and ski resort in the Haute-Savoie region, famous for its dramatic mountain scenery and mountaineering history.
-
D.
Satigny
Satigny is a Swiss municipality in the canton of Geneva, known for being one of the country’s largest wine-producing communes.
-
E.
Mossenberg-Wöhren
Mossenberg-Wöhren is a small village in North Rhine-Westphalia, Germany, known primarily as the birthplace of former German chancellor Gerhard Schröder.
- 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25cadae1c8190be0e8dcf33351187 |
completed | Feb. 28, 2026, 3:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4239b5dfc8190930c379823e42139 |
completed | March 1, 2026, 11:31 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.