Triple
T12284535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dark ’n’ Stormy |
E292794
|
entity |
| Predicate | isCommonlyGarnishedWith |
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: [Dark ’n’ Stormy, isCommonlyGarnishedWith, lime wedge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCommonlyGarnishedWith Context triple: [Dark ’n’ Stormy, isCommonlyGarnishedWith, lime wedge]
-
A.
isTypicallyGarnishedWith
chosen
Indicates that one item is commonly used as a garnish or decorative finishing element for another.
-
B.
isUsuallyCookedIn
Indicates that something is most commonly or typically prepared or cooked within a particular container, appliance, or environment.
-
C.
usesIngredient
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
D.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
-
E.
seasoningStyle
Indicates the characteristic way in which an item is flavored or seasoned, such as the method, intensity, or cultural style of its seasoning.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9261e1570819084bb4fdb44aa6aea |
completed | April 10, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69d91c4d9a9c8190aeb7beaf9792d8f0 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.