Triple
T704761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Veeder AVA |
E14074
|
entity |
| Predicate | grapeColorFocus |
P12088
|
FINISHED |
| Object | red wine grapes |
—
|
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: red wine grapes | Statement: [Mount Veeder AVA, grapeColorFocus, red wine grapes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grapeColorFocus Context triple: [Mount Veeder AVA, grapeColorFocus, red wine grapes]
-
A.
wineColor
chosen
Indicates the color attribute or hue associated with a given wine.
-
B.
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).
-
C.
viticulturalFocus
Indicates a focus on or specialization in viticulture, i.e., activities, practices, or interests centered on grape growing and vineyard management.
-
D.
usesGrapeType
Indicates that one entity employs or incorporates a specific type or variety of grape in its composition, production, or process.
-
E.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a58d4c3c8190ad4527d14bca5e6e |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4edc33881909a978268f6dd5d82 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.