Triple
T17915741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bigorre black pork |
E447920
|
entity |
| Predicate | cookingUse |
P14777
|
FINISHED |
| Object | roasting |
—
|
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: roasting | Statement: [Bigorre black pork, cookingUse, roasting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cookingUse Context triple: [Bigorre black pork, cookingUse, roasting]
-
A.
culinaryUse
Indicates that one entity is used in the preparation, flavoring, or serving of food or drink for another entity.
-
B.
usesCookingMethod
chosen
Indicates that one entity prepares or processes another entity by applying a specific cooking technique or method.
-
C.
isUsuallyCookedIn
Indicates that something is most commonly or typically prepared or cooked within a particular container, appliance, or environment.
-
D.
usesRecipeOf
Indicates that one entity prepares or creates something by following the recipe or formula originally defined or used by another entity.
-
E.
usesIngredient
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a3054f048190a98a3b314cd82d5c |
completed | April 19, 2026, 9:40 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
Created at: April 10, 2026, 10:20 a.m.