Triple
T2958013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blanc Fumé |
E79978
|
entity |
| Predicate | primaryGrapeUse |
P45198
|
FINISHED |
| Object | still white wine |
—
|
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: still white wine | Statement: [Blanc Fumé, primaryGrapeUse, still white wine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryGrapeUse Context triple: [Blanc Fumé, primaryGrapeUse, still white wine]
-
A.
primaryGrapeVariety
Indicates that one entity is the main or predominant grape variety used in producing the other entity (typically a wine or wine-based product).
-
B.
secondaryGrape
Indicates that one grape variety serves as a secondary or supporting component in a wine blend relative to the primary grape.
-
C.
traditionalGrapeVariety
Indicates that a grape variety is traditionally or historically used in a specific region, wine style, or cultural winemaking practice.
-
D.
viticulturalFocus
Indicates a focus on or specialization in viticulture, i.e., activities, practices, or interests centered on grape growing and vineyard management.
-
E.
usesGrapeType
Indicates that one entity employs or incorporates a specific type or variety of grape in its composition, production, or process.
- 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_69ad8b1276588190a374a0b12e0f7bdf |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad992b33e081909d22a19d5064c47d |
completed | March 8, 2026, 3:43 p.m. |
| PD | Predicate disambiguation | batch_69ad960c5c8881909d679912bd7d78f3 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad98379fac8190a4dfe530787703c9 |
completed | March 8, 2026, 3:39 p.m. |
Created at: March 8, 2026, 2:57 p.m.