Triple
T86842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgians |
E1745
|
entity |
| Predicate | traditionalDrink |
P4038
|
FINISHED |
| Object | Georgian 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: Georgian wine | Statement: [Georgians, traditionalDrink, Georgian wine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalDrink Context triple: [Georgians, traditionalDrink, Georgian wine]
-
A.
wineStyle
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
-
B.
traditionalCuisine
Indicates that an entity is associated with the customary or historically rooted style of cooking and food preparation characteristic of a particular culture, region, or community.
-
C.
domesticCup
Indicates that an entity has won or participated in a domestic (national-level) cup competition within its sport or domain.
-
D.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
E.
alcoholLevel
Indicates the measured concentration or amount of alcohol present in an entity (such as a person, substance, or environment).
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2503d304c8190a0034ffa4a38a501 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb6da2c8190a33d144d219f7abe |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a2503c12808190a3cbb7b171f466f0 |
completed | Feb. 28, 2026, 2:17 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.