Triple
T11021710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château Carbonnieux |
E260504
|
entity |
| Predicate | redVineyardArea |
P44612
|
FINISHED |
| Object | approximately 50 hectares |
—
|
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: approximately 50 hectares | Statement: [Château Carbonnieux, redVineyardArea, approximately 50 hectares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: redVineyardArea Context triple: [Château Carbonnieux, redVineyardArea, approximately 50 hectares]
-
A.
vineyardSize
chosen
Indicates the extent or area of land occupied by a vineyard.
-
B.
viticulturalAreaCode
Indicates the designated code that identifies the specific viticultural (wine-producing) area associated with an entity.
-
C.
viticulturalAreaDesignation
Indicates that a specific geographic area is officially designated or recognized for viticulture (grape growing and wine production).
-
D.
viticulturalAreaType
Indicates the specific type or classification of a viticultural area associated with an entity.
-
E.
vineyardAreaRankInFrance
Indicates the relative position of an entity’s vineyard area compared to other vineyard areas within France, ordered by size.
- 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797bb6eec81909d8004af31f307f7 |
completed | April 9, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69d72e995e008190bbffb314129ed0cd |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:25 p.m.