Triple
T18683793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Côte AOC |
E456801
|
entity |
| Predicate | hasViticulturalTradition |
P59581
|
FINISHED |
| Object | long-established |
—
|
LITERAL 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: long-established | Statement: [La Côte AOC, hasViticulturalTradition, long-established]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViticulturalTradition Context triple: [La Côte AOC, hasViticulturalTradition, long-established]
-
A.
hasWineMakingTradition
chosen
Indicates that a place or group has an established, culturally recognized history and practice of producing wine.
-
B.
hasViticulturalImportance
Indicates that something plays a significant role or has notable relevance in the cultivation and production of grapes for wine.
-
C.
hasVineyards
Indicates that one entity possesses, contains, or is associated with vineyards used for growing grapevines.
-
D.
hasVineyardsNear
Indicates that one entity possesses or is associated with vineyards located in close geographic proximity to another entity.
-
E.
hasWinemakingFacility
Indicates that an entity possesses or is associated with a facility where winemaking activities are carried out.
- F. None of above.
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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55b2b819c8190b5f3d7a88607f6f5 |
completed | April 19, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69e478db7a248190a8c6584673773923 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:49 a.m.