Triple
T11473903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giada at Home |
E271976
|
entity |
| Predicate | typicalDishType |
P19483
|
FINISHED |
| Object | pasta dishes |
—
|
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: pasta dishes | Statement: [Giada at Home, typicalDishType, pasta dishes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDishType Context triple: [Giada at Home, typicalDishType, pasta dishes]
-
A.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
B.
traditionalDish
chosen
Indicates that the object is a dish customarily prepared, eaten, or recognized within the subject’s cultural or regional tradition.
-
C.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
-
D.
isTypicallyServedFor
Indicates that one item is most commonly or customarily served as a meal or course for the other (e.g., a dish typically served for breakfast, lunch, or dinner).
-
E.
feastType
Indicates the specific kind or category of feast associated with an event or occasion.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8294b3f388190a587c358313f7260 |
completed | April 9, 2026, 10:33 p.m. |
| PD | Predicate disambiguation | batch_69d8086ecd6c81908f424864857762d6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:35 p.m.