Triple
T25637600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corona Premier |
E642747
|
entity |
| Predicate | recommendedGarnish |
P56695
|
FINISHED |
| Object | lime wedge |
—
|
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: lime wedge | Statement: [Corona Premier, recommendedGarnish, lime wedge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recommendedGarnish Context triple: [Corona Premier, recommendedGarnish, lime wedge]
-
A.
isTypicallyGarnishedWith
chosen
Indicates that one item is commonly used as a garnish or decorative finishing element for another.
-
B.
seasoningType
Indicates the specific kind or category of seasoning associated with an item or preparation.
-
C.
seasoningStyle
Indicates the characteristic way in which an item is flavored or seasoned, such as the method, intensity, or cultural style of its seasoning.
-
D.
usesIngredient
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
E.
intendedMeal
Indicates that one entity is the meal that another entity plans or expects to eat.
- 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_69e77e7ce28081908b08d65ee6e5c8be |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fa6345548190a52498ecb0a2f555 |
completed | May 2, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69f4938262ac8190b41f922d0407d272 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 21, 2026, 5:34 p.m.