Triple
T12284554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dark ’n’ Stormy |
E292794
|
entity |
| Predicate | isNonHotBeverage |
P104040
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Dark ’n’ Stormy, isNonHotBeverage, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNonHotBeverage Context triple: [Dark ’n’ Stormy, isNonHotBeverage, true]
-
A.
isPackagedBeverage
Indicates that an item is a beverage that has been contained or sealed within some form of packaging for distribution or consumption.
-
B.
hasBeverageCategory
Indicates that an entity is associated with or classified under a particular beverage category.
-
C.
hasCaffeineContent
Indicates that one entity (typically a beverage or substance) possesses a specified amount or presence of caffeine.
-
D.
hasCaffeineFreeOption
Indicates that something offers an available version or option that does not contain caffeine.
-
E.
beverageSubcategory
Indicates a more specific classification within a broader beverage category, defining the subtype or subcategory of a drink.
- 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_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. |
| PDg | Predicate description generation | batch_69d9261b7f088190b69fe6961015fce3 |
completed | April 10, 2026, 4:32 p.m. |
Created at: April 8, 2026, 9:52 p.m.