Triple
T17057203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paula Deen’s Family Kitchen |
E413854
|
entity |
| Predicate | hasDessertType |
P90648
|
FINISHED |
| Object | cobblers |
—
|
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: cobblers | Statement: [Paula Deen’s Family Kitchen, hasDessertType, cobblers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDessertType Context triple: [Paula Deen’s Family Kitchen, hasDessertType, cobblers]
-
A.
hasDessert
chosen
Indicates that one entity is served, accompanied, or associated with a particular dessert item.
-
B.
hasDishType
Indicates that an item (such as a food or menu entry) is classified as belonging to a particular type of dish (e.g., appetizer, main course, dessert).
-
C.
pastryType
Indicates the specific kind or category of pastry that an item belongs to.
-
D.
hasTypeOfIndulgence
Indicates that an entity is associated with a specific kind or category of indulgence it involves or permits.
-
E.
hasFruitType
Indicates that an entity possesses or is associated with a specific type or category of fruit.
- 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.