Triple
T37240238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinotage |
E923691
|
entity |
| Predicate | associatedWineIndustry |
P201855
|
FINISHED |
| Object | South African wine industry |
—
|
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: South African wine industry | Statement: [Pinotage, associatedWineIndustry, South African wine industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWineIndustry Context triple: [Pinotage, associatedWineIndustry, South African wine industry]
-
A.
associatedWithWineProduction
chosen
Indicates a relationship where an entity is involved in, connected to, or plays a role in the production of wine.
-
B.
wineEconomyRole
Indicates the role or function an entity has within the wine-related economy, such as production, distribution, trade, or regulation.
-
C.
alsoProducesWineIn
Indicates that the subject, in addition to other products or activities, produces wine in the specified location or context.
-
D.
notableWine
Indicates that a wine is recognized as significant, distinguished, or noteworthy in some context (such as quality, reputation, or historical importance).
-
E.
producesWine
Indicates that one entity creates or manufactures wine as a product.
- 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_69f76ea9fee88190a589f661d95a7189 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:15 p.m.