Triple
T27811187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milk Stand |
E702521
|
entity |
| Predicate | basedOnFictionalBeverageType |
P182222
|
FINISHED |
| Object | bantha milk |
—
|
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: bantha milk | Statement: [Milk Stand, basedOnFictionalBeverageType, bantha milk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnFictionalBeverageType Context triple: [Milk Stand, basedOnFictionalBeverageType, bantha milk]
-
A.
basedOnFictionalBeverageFrom
chosen
Indicates that something is derived from, inspired by, or modeled after a fictional beverage originating in a specified source.
-
B.
beverageBase
Indicates that one entity serves as the primary liquid or foundational ingredient used to make a beverage involving the other entity.
-
C.
hasBeverageProduct
Indicates that one entity possesses, offers, or is associated with a particular beverage product.
-
D.
isSoftDrinkVariantOf
Indicates that one soft drink is a specific version, flavor, or formulation derived from or based on another soft drink.
-
E.
hasBeverageReference
Indicates that one entity makes reference to, mentions, or is associated with a beverage in some way.
- 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_69ef840a16748190926719ab96120bae |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f78c61ed4c8190ad84c918fa9af55a |
completed | May 3, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
Created at: April 27, 2026, 5:42 p.m.