Triple
T12284974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow Mule |
E292804
|
entity |
| Predicate | hasTypicalServingSize |
P3664
|
FINISHED |
| Object | about 8–12 US fluid ounces |
—
|
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: about 8–12 US fluid ounces | Statement: [Moscow Mule, hasTypicalServingSize, about 8–12 US fluid ounces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalServingSize Context triple: [Moscow Mule, hasTypicalServingSize, about 8–12 US fluid ounces]
-
A.
hasCalories
Indicates that an entity contains a specified amount of caloric energy.
-
B.
servingSizeAtOktoberfest
Indicates the typical quantity or portion in which something (such as food or drink) is served specifically at Oktoberfest.
-
C.
typicalUnitSize
chosen
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
-
D.
isTypicallyGarnishedWith
Indicates that one item is commonly used as a garnish or decorative finishing element for another.
-
E.
carbohydratesPer12Ounces
Indicates the amount of carbohydrates contained in a 12-ounce serving of a given item.
- 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.