Triple
T29502695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kraft Macaroni & Cheese |
E748416
|
entity |
| Predicate | oftenRequiresAddedIngredient |
P12771
|
FINISHED |
| Object | 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: milk | Statement: [Kraft Macaroni & Cheese, oftenRequiresAddedIngredient, milk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenRequiresAddedIngredient Context triple: [Kraft Macaroni & Cheese, oftenRequiresAddedIngredient, milk]
-
A.
usesIngredient
chosen
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
B.
isTypicallyGarnishedWith
Indicates that one item is commonly used as a garnish or decorative finishing element for another.
-
C.
usesIngredientInfluenceFrom
Indicates that one entity incorporates or applies the influence, properties, or effects derived from a particular ingredient in its action or outcome.
-
D.
hasMainIngredient
Indicates that one entity is the primary or most significant ingredient used to make another entity.
-
E.
isTypicallyEatenWith
Indicates that one item is commonly consumed together with another as part of the same eating occasion or dish.
- 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_69f0bd455a9c8190b40a3e8ea38cf61f |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 28, 2026, 4:25 p.m.