Triple
T9866005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burgundy AOC wines |
E239833
|
entity |
| Predicate | keyTerroirFactor |
P42963
|
FINISHED |
| Object | limestone soils |
—
|
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: limestone soils | Statement: [Burgundy AOC wines, keyTerroirFactor, limestone soils]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: keyTerroirFactor Context triple: [Burgundy AOC wines, keyTerroirFactor, limestone soils]
-
A.
viticulturalCharacteristic
Indicates a relationship where a specific trait, quality, or property is attributed to viticulture or grape-growing practices.
-
B.
viticulturalFeature
chosen
Indicates a characteristic, condition, or attribute specifically related to grape growing or vineyard cultivation.
-
C.
oenologicalSignificance
Indicates the relationship in which something holds importance, relevance, or notable impact within the context of wine or winemaking.
-
D.
viticulturalFocus
Indicates a focus on or specialization in viticulture, i.e., activities, practices, or interests centered on grape growing and vineyard management.
-
E.
wineCharacteristic
Indicates a descriptive property or quality attributed to a wine, such as its flavor, aroma, color, or style.
- 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_69ca84e7506c819095cbde4ff16512bb |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3d091e48190b10463562d0dc461 |
completed | April 2, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:36 p.m.