Triple
T15447900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Côte wine region |
E370071
|
entity |
| Predicate | hasSubregion |
P285
|
FINISHED |
| Object | Rolle |
E100491
|
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: Rolle | Statement: [La Côte wine region, hasSubregion, Rolle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rolle Context triple: [La Côte wine region, hasSubregion, Rolle]
-
A.
Rolle
chosen
Rolle is a picturesque Swiss town on the shores of Lake Geneva, known for its lakeside promenade, historic castle, and surrounding vineyards.
-
B.
Roal
Roal is a small settlement located in the Hadeland district of southeastern Norway.
-
C.
Rollot
Rollot is a small commune in northern France, notable as the birthplace of the orientalist and translator Antoine Galland.
-
D.
Rolen
Rolen is a surname most notably associated with Scott Rolen, a Hall of Fame Major League Baseball third baseman.
-
E.
René
René is a French given name commonly used for males and historically associated with several notable figures in politics, arts, and philosophy.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ef767b4819099f2c0919a158321 |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21afb6f4819094162ca842b7eb60 |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:21 a.m.