Triple
T12284965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow Mule |
E292804
|
entity |
| Predicate | isTypicallyConsumed |
P97073
|
FINISHED |
| Object | cold |
—
|
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: cold | Statement: [Moscow Mule, isTypicallyConsumed, cold]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTypicallyConsumed Context triple: [Moscow Mule, isTypicallyConsumed, cold]
-
A.
isConsumedIn
Indicates that one entity is used up, ingested, or otherwise expended as part of a process, event, or action involving another entity.
-
B.
isConsumedBy
Indicates that one entity is eaten, drunk, or otherwise ingested or used up by another entity.
-
C.
isEatenFor
Indicates that one entity is consumed as food for the benefit, nourishment, or use of another entity.
-
D.
typicalSettingConsumed
chosen
Indicates the usual context or environment in which something is normally consumed.
-
E.
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).
- 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.