Triple
T31041856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canterbury wine region |
E791014
|
entity |
| Predicate | primaryWineColour |
P12088
|
FINISHED |
| Object | red wine |
—
|
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: red wine | Statement: [Canterbury wine region, primaryWineColour, red wine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryWineColour Context triple: [Canterbury wine region, primaryWineColour, red wine]
-
A.
wineColor
chosen
Indicates the color attribute or hue associated with a given wine.
-
B.
wineColorMajority
Indicates that the majority of a given set or collection of wines share the same color.
-
C.
wineColorOptions
Indicates the set of possible color categories that can be associated with a given wine.
-
D.
grapeColorForRosé
Indicates that a particular grape color is used in the production of rosé wine.
-
E.
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).
- 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_69f224ca2fa881908a3ac5fedf207b90 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:59 p.m.