Triple
T1185583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knights Valley AVA |
E25236
|
entity |
| Predicate | appellationType |
P25011
|
FINISHED |
| Object | viticultural area |
—
|
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: viticultural area | Statement: [Knights Valley AVA, appellationType, viticultural area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appellationType Context triple: [Knights Valley AVA, appellationType, viticultural area]
-
A.
notableAppellation
Indicates that an entity is known by, or commonly referred to with, a particular notable name or title.
-
B.
wineClassificationSystem
Indicates a system or scheme used to categorize and organize wines based on defined criteria such as origin, style, or quality.
-
C.
wineStyle
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
-
D.
wineStructure
Indicates the overall sensory framework of a wine, encompassing how its components like acidity, tannin, body, and alcohol are balanced and interact.
-
E.
wineRegion
Indicates the geographical region or area where a particular wine is produced or originates.
- 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd39245881908766c41943dc2752 |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb59ca6c81908597a81646674aaa |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bc6d5b7881908091e40c8695ef53 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:45 p.m.