Triple
T4551513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portugal and Spain |
E110173
|
entity |
| Predicate | haveWineTraditions |
P26577
|
FINISHED |
| Object | prominent |
—
|
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: prominent | Statement: [Portugal and Spain, haveWineTraditions, prominent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveWineTraditions Context triple: [Portugal and Spain, haveWineTraditions, prominent]
-
A.
nationalWineTradition
chosen
Indicates that a country or region has an established cultural and historical practice of producing, consuming, and valuing wine.
-
B.
wineTourism
Indicates a relationship where tourism activities are specifically centered around visiting wine-producing regions, wineries, and related wine experiences.
-
C.
producesWine
Indicates that one entity creates or manufactures wine as a product.
-
D.
wineLaw
Indicates a legal or regulatory relationship governing the production, sale, labeling, or distribution of wine.
-
E.
wineStylesAssociatedWith
Indicates a relationship where certain wine styles are linked or connected to a particular entity, such as a region, grape, producer, or 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57f7b9748190af29d02fc77b02e0 |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5223423c81908317351b58cff5f5 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:05 p.m.