Triple
T17761395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cabrières |
E443383
|
entity |
| Predicate | grapeVarietyUsed |
P975
|
FINISHED |
| Object | Cinsaut |
—
|
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: Cinsaut | Statement: [Cabrières, grapeVarietyUsed, Cinsaut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cinsaut Context triple: [Cabrières, grapeVarietyUsed, Cinsaut]
-
A.
Cinsaut
chosen
Cinsaut is a red wine grape variety from southern France, known for producing soft, fruity wines and often used in blends and rosé.
-
B.
Hippolais
Hippolais is a genus of small insectivorous warblers found mainly in Europe, North Africa, and western Asia.
-
C.
Mouton-Duvernet
Mouton-Duvernet is a Paris Métro station in the 14th arrondissement, serving the Montparnasse area and named after the French general Régis Barthélemy Mouton-Duvernet.
-
D.
Lasauvage
Lasauvage is a small village in southwestern Luxembourg, known for its historical iron-mining heritage and proximity to the industrial town of Differdange.
-
E.
Cesqeaux
Cesqeaux is a Dutch DJ and electronic music producer known for his energetic trap and bass-heavy festival tracks.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e485f7a8e08190a4a6b8368b70c381 |
completed | April 19, 2026, 7:36 a.m. |
Created at: April 10, 2026, 10:11 a.m.