Triple
T11499119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Geneva region |
E272617
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Vevey |
E52386
|
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: Vevey | Statement: [Lake Geneva region, hasPart, Vevey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vevey Context triple: [Lake Geneva region, hasPart, Vevey]
-
A.
Vevey
chosen
Vevey is a picturesque Swiss town in the canton of Vaud, known for its lakeside setting, association with Charlie Chaplin, and role as the headquarters of Nestlé.
-
B.
Broye-Vully
Broye-Vully is an administrative district in the canton of Vaud in western Switzerland, known for its rural landscapes, agriculture, and wine-producing areas.
-
C.
Côtes de Genève
Côtes de Genève is a traditional decorative finishing technique used in Swiss watchmaking, characterized by parallel wave-like stripes engraved on movement components.
-
D.
Murten
Murten is a historic bilingual town in the canton of Fribourg, Switzerland, known for its well-preserved medieval old town and lakeside setting on Lake Murten.
-
E.
Saignelégier
Saignelégier is a municipality in the Swiss canton of Jura known for its rural landscapes, watchmaking heritage, and the annual Marché-Concours horse festival.
- 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_69d6aae1b09881909ce2ded3fa0c14fa |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85de27db081909ccdb4ab0ef75bdb |
completed | April 10, 2026, 2:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e604aa9e3c8190ad86e4d05a67c8ac |
completed | April 20, 2026, 10:49 a.m. |
Created at: April 8, 2026, 9:36 p.m.