Triple
T12714689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinon AOC |
E303805
|
entity |
| Predicate | roséShare |
P106312
|
FINISHED |
| Object | small proportion of production |
—
|
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: small proportion of production | Statement: [Chinon AOC, roséShare, small proportion of production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roséShare Context triple: [Chinon AOC, roséShare, small proportion of production]
-
A.
roséWineAllowed
Indicates that the consumption or presence of rosé wine is permitted in the given context or under the specified conditions.
-
B.
grapeColorForRosé
Indicates that a particular grape color is used in the production of rosé wine.
-
C.
whiteWineShare
Indicates the proportion or share of white wine within a larger set, such as total wine consumption, production, or sales.
-
D.
wineColor
Indicates the color attribute or hue associated with a given wine.
-
E.
roséWineProductionAllowed
Indicates that the production of rosé wine is permitted under the relevant rules or conditions.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9620a7554819083784897ff690652 |
completed | April 10, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69d960c088dc8190b0e63312c54e4c6c |
completed | April 10, 2026, 8:42 p.m. |
| PDg | Predicate description generation | batch_69d961acadb8819098de743bc951fedb |
completed | April 10, 2026, 8:46 p.m. |
Created at: April 9, 2026, 5:23 p.m.