Triple
T12754636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgium and France |
E304824
|
entity |
| Predicate | sharesWineAndBeerCulture |
P106723
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Belgium and France, sharesWineAndBeerCulture, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesWineAndBeerCulture Context triple: [Belgium and France, sharesWineAndBeerCulture, yes]
-
A.
nationalWineTradition
Indicates that a country or region has an established cultural and historical practice of producing, consuming, and valuing wine.
-
B.
wineCountry
Indicates that a location is recognized as a region where wine is produced, typically known for its vineyards and wineries.
-
C.
wineLaw
Indicates a legal or regulatory relationship governing the production, sale, labeling, or distribution of wine.
-
D.
wineTourism
Indicates a relationship where tourism activities are specifically centered around visiting wine-producing regions, wineries, and related wine experiences.
-
E.
notableWine
Indicates that a wine is recognized as significant, distinguished, or noteworthy in some context (such as quality, reputation, or historical importance).
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96406e97c8190b79081039847115c |
completed | April 10, 2026, 8:56 p.m. |
| PDg | Predicate description generation | batch_69d96d87078c819083ea724238992204 |
completed | April 10, 2026, 9:37 p.m. |
Created at: April 9, 2026, 5:27 p.m.