Triple
T31723396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château Cheval Blanc |
E809643
|
entity |
| Predicate | architectOfWinery |
P183135
|
FINISHED |
| Object | Christian de Portzamparc |
—
|
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: Christian de Portzamparc | Statement: [Château Cheval Blanc, architectOfWinery, Christian de Portzamparc]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: architectOfWinery Context triple: [Château Cheval Blanc, architectOfWinery, Christian de Portzamparc]
-
A.
hasWinemaker
Indicates that one entity serves as the winemaker responsible for producing or overseeing the production of wine for another entity.
-
B.
notableWinemaker
Indicates that the subject is recognized as a distinguished or prominent winemaker.
-
C.
oenologist
Indicates that one entity is an expert in the science and practice of wine and winemaking in relation to another entity.
-
D.
hasWinery
Indicates a relationship where a subject owns, operates, or is associated with a particular winery.
-
E.
producesWine
Indicates that one entity creates or manufactures wine as a product.
- F. None of above. chosen
Provenance (4 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_69f348e009c8819095d77df52c645b9c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f798387ea481909f51303f53a22e52 |
completed | May 3, 2026, 6:47 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
| PDg | Predicate description generation | batch_69f79798663481908d6bc48dd6a94ca6 |
completed | May 3, 2026, 6:44 p.m. |
Created at: April 30, 2026, 11:19 p.m.