Triple
T29551031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philadelphia Cream Cheese |
E749766
|
entity |
| Predicate | commonlyUsedIngredientIn |
P12771
|
FINISHED |
| Object | New York–style cheesecake |
—
|
NE NERFINISHED |
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: New York–style cheesecake | Statement: [Philadelphia Cream Cheese, commonlyUsedIngredientIn, New York–style cheesecake]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonlyUsedIngredientIn Context triple: [Philadelphia Cream Cheese, commonlyUsedIngredientIn, New York–style cheesecake]
-
A.
usesIngredient
chosen
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
B.
ingredientType
Indicates that one entity is classified as a specific type or category of ingredient in relation to 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.
culinaryUse
Indicates that one entity is used in the preparation, flavoring, or serving of food or drink for another entity.
-
E.
typicalIngredientRatio
Indicates the usual proportional relationship between different ingredients used together in a preparation or mixture.
- 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_69f0bd48691081908cecad39bac591e0 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
Created at: April 28, 2026, 5:12 p.m.