Triple
T3853561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Languedoc AOC |
E85355
|
entity |
| Predicate | typicalRoséBaseGrapes |
P28269
|
FINISHED |
| Object | Grenache |
—
|
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: Grenache | Statement: [Languedoc AOC, typicalRoséBaseGrapes, Grenache]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRoséBaseGrapes Context triple: [Languedoc AOC, typicalRoséBaseGrapes, Grenache]
-
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.
traditionalGrapeVariety
chosen
Indicates that a grape variety is traditionally or historically used in a specific region, wine style, or cultural winemaking practice.
-
C.
grapeColorProduced
Indicates the color that is produced by or characteristic of a given grape.
-
D.
grapeColorForReds
Indicates that the predicate specifies the typical color of grapes used to produce red wines.
-
E.
roséWineAllowed
Indicates that the consumption or presence of rosé wine is permitted in the given context or under the specified conditions.
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec0438308190865ff74bee5a1cf2 |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.