Triple
T12284522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dark ’n’ Stormy |
E292794
|
entity |
| Predicate | isTypicallyServedIn |
P104034
|
FINISHED |
| Object | highball glass |
—
|
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: highball glass | Statement: [Dark ’n’ Stormy, isTypicallyServedIn, highball glass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTypicallyServedIn Context triple: [Dark ’n’ Stormy, isTypicallyServedIn, highball glass]
-
A.
isTypicallyServedFor
Indicates that one item is most commonly or customarily served as a meal or course for the other (e.g., a dish typically served for breakfast, lunch, or dinner).
-
B.
servesType
Indicates that one entity provides, offers, or is used to deliver a particular type, category, or kind of thing or service.
-
C.
servesMostly
Indicates that one entity primarily functions to serve, support, or cater to another entity, more than to any other.
-
D.
typicallyServedAs
Indicates that something is most commonly presented, used, or offered in a particular role, form, or function.
-
E.
isServedAt
Indicates that something (such as food, drink, or a service) is provided or made available at a particular place or venue.
- 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.