Triple
T1159563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cajun cuisine |
E24462
|
entity |
| Predicate | usesIngredientGroup |
P12771
|
FINISHED |
| Object | the Holy Trinity of Cajun cooking |
—
|
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: the Holy Trinity of Cajun cooking | Statement: [Cajun cuisine, usesIngredientGroup, the Holy Trinity of Cajun cooking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesIngredientGroup Context triple: [Cajun cuisine, usesIngredientGroup, the Holy Trinity of Cajun cooking]
-
A.
usesIngredient
chosen
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
B.
hasMainIngredient
Indicates that one entity is the primary or most significant ingredient used to make another entity.
-
C.
usesCookingMethod
Indicates that one entity prepares or processes another entity by applying a specific cooking technique or method.
-
D.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
-
E.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcad47a08190895769611798f67f |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb525b648190adcb7a29256d3c41 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:45 p.m.