Triple
T31703996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château Pavie |
E809130
|
entity |
| Predicate | oenologicalProfile |
P20482
|
FINISHED |
| Object | high tannin structure |
—
|
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: high tannin structure | Statement: [Château Pavie, oenologicalProfile, high tannin structure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oenologicalProfile Context triple: [Château Pavie, oenologicalProfile, high tannin structure]
-
A.
oenologicalSignificance
Indicates the relationship in which something holds importance, relevance, or notable impact within the context of wine or winemaking.
-
B.
oenologicalPractice
Indicates a relationship where an entity is involved in, applies, or is characterized by a specific winemaking or wine-handling practice.
-
C.
oenologist
Indicates that one entity is an expert in the science and practice of wine and winemaking in relation to another entity.
-
D.
wineStructure
chosen
Indicates the overall sensory framework of a wine, encompassing how its components like acidity, tannin, body, and alcohol are balanced and interact.
-
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_69f348de914081909fc8edff56f34dbe |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6aaf50be08190a2b62a6d881f8aee |
completed | May 3, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:13 p.m.