Triple
T2441269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doux |
E53280
|
entity |
| Predicate | hasRelativeSweetness |
P2068
|
FINISHED |
| Object | sweetest style of Champagne |
—
|
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: sweetest style of Champagne | Statement: [Doux, hasRelativeSweetness, sweetest style of Champagne]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelativeSweetness Context triple: [Doux, hasRelativeSweetness, sweetest style of Champagne]
-
A.
hasSugarContent
Indicates that one entity possesses or contains a specified amount or level of sugar.
-
B.
allowsTastingOf
Indicates that one entity permits another entity to sample or try the taste of something.
-
C.
hasSpiciness
Indicates that one entity possesses a certain level or quality of spiciness in relation to another entity or a defined scale.
-
D.
typicalFlavor
chosen
Indicates that something characteristically has or is associated with a particular flavor.
-
E.
traditionalSweet
Indicates that something is a sweet food or dessert prepared according to long-established customs or cultural traditions.
- 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_69ab495b6dac8190ac82661aa1452222 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcebf7cac8190889e6890d72c256c |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5ac11b081908ce6a506e81a742a |
completed | March 7, 2026, 6:29 a.m. |
Created at: March 6, 2026, 9:43 p.m.