Triple
T17057189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paula Deen’s Family Kitchen |
E413854
|
entity |
| Predicate | hasDietaryFocus |
P44705
|
FINISHED |
| Object | butter-rich recipes |
—
|
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: butter-rich recipes | Statement: [Paula Deen’s Family Kitchen, hasDietaryFocus, butter-rich recipes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDietaryFocus Context triple: [Paula Deen’s Family Kitchen, hasDietaryFocus, butter-rich recipes]
-
A.
characterizesDietAs
Indicates that one entity describes, defines, or assigns the type or nature of another entity’s diet.
-
B.
dietaryOptions
Indicates the types of diets or food-related preferences, restrictions, or choices that are applicable to or offered for an entity.
-
C.
hasDietaryLaw
Indicates that one entity prescribes, follows, or is governed by a specific set of dietary rules or restrictions associated with another entity.
-
D.
focusesOnNutrition
chosen
Indicates that the subject’s primary attention, activity, or content is centered on nutrition-related topics, practices, or goals.
-
E.
nutritionType
Indicates the specific category or kind of nutritional characteristic or value associated with an 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3db7a96288190bd985f79c3f55623 |
completed | April 18, 2026, 7:28 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:34 a.m.