Triple
T23102584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Savagnin Blanc |
E576072
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Savagnin |
—
|
NE NERFINISHED |
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: Savagnin | Statement: [Savagnin Blanc, alsoKnownAs, Savagnin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Savagnin Context triple: [Savagnin Blanc, alsoKnownAs, Savagnin]
-
A.
Savagnin
chosen
Savagnin is a white wine grape variety traditionally grown in France’s Jura region, known for producing distinctive, nutty, and oxidative-style wines such as vin jaune.
-
B.
Bergognone
Bergognone was an Italian Renaissance painter from Lombardy, known for his serene religious works and contributions to the Lombard school of painting.
-
C.
Scorzè
Scorzè is a municipality in the Veneto region of northeastern Italy, situated inland near Venice and known for its agricultural landscape and small-town character.
-
D.
Oeschgen
Oeschgen is a small Swiss municipality in the Fricktal region of the canton of Aargau.
-
E.
Sorengo
Sorengo is a small municipality in the canton of Ticino in southern Switzerland, located near Lugano.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245c060b48190a9bd61a47a16db17 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18de9fa8c81909fd26ff37173b85b |
completed | April 29, 2026, 4:49 a.m. |
Created at: April 17, 2026, 3:58 p.m.