Triple
T13972588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elbling |
E336100
|
entity |
| Predicate | wineMarketRole |
P53749
|
FINISHED |
| Object | regionalSpecialty |
—
|
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: regionalSpecialty | Statement: [Elbling, wineMarketRole, regionalSpecialty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineMarketRole Context triple: [Elbling, wineMarketRole, regionalSpecialty]
-
A.
wineMarket
Indicates a commercial context or marketplace where wine is bought, sold, or traded.
-
B.
wineEconomyRole
chosen
Indicates the role or function an entity has within the wine-related economy, such as production, distribution, trade, or regulation.
-
C.
wineRegionRole
Indicates the specific role or function that a wine-producing region has in relation to wine production, classification, or designation.
-
D.
wineReputation
Indicates the perceived quality, prestige, or standing of a wine based on expert opinion, consumer perception, or historical recognition.
-
E.
wineRegionSpecialization
Indicates a relationship where a wine-producing region is characterized by or particularly known for specializing in a specific type or style of wine.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8eae40819080dd4bd25c73b6d6 |
completed | April 14, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69dd465a21408190b912a42c50ffa0d9 |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.