Triple
T15351487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Côte |
E367062
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Founex |
E437777
|
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: Founex | Statement: [La Côte, hasTown, Founex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Founex Context triple: [La Côte, hasTown, Founex]
-
A.
Founex
chosen
Founex is a small Swiss municipality on Lake Geneva in the canton of Vaud, known for its residential character and proximity to 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.
Finavon
Finavon is a small village in Angus, Scotland, known for its historic castle ruins and scenic position near the River South Esk.
-
D.
Nucourt
Nucourt is a small commune in the Val-d'Oise department in the Île-de-France region of northern France.
-
E.
Fezco
Fezco is a soft-spoken teenage drug dealer and loyal friend character from the television series "Euphoria."
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e290efc8190b22c95dcd3e5f57f |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01fd53688190939787a3d6ff3bb9 |
completed | May 9, 2026, 9:44 a.m. |
Created at: April 10, 2026, 3:17 a.m.